diff --git "a/data/benchmarks.csv" "b/data/benchmarks.csv"
new file mode 100644--- /dev/null
+++ "b/data/benchmarks.csv"
@@ -0,0 +1,317 @@
+benchmark_id,benchmark_name,category,metric,num_problems,source_url,canonical_setting_json,in_paper_matrix
+agentcompany,AgentCompany,Agentic,%,,https://huggingface.co/MiniMaxAI/MiniMax-M2,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per MiniMax M2 model card."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""AgentCompany""}",False
+apex_agents,APEX-Agents,Agentic,,,https://deepmind.google/models/evals-methodology/gemini-3-pro,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""DeepMind APEX-Agents long-horizon professional benchmark. Distinct from MathArena Apex 2025."", ""range"": [0, 100], ""version"": ""APEX-Agents (long-horizon professional tasks)""}",False
+browsecomp,BrowseComp,Agentic,% correct,1266.0,https://openai.com/index/browsecomp/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=agentic (scaffold-defined). Preferred = official harness tools (bash/editor for SWE-bench, browser for OSWorld/BrowseComp, official APIs for tau-bench/MCPAtlas/Toolathlon, terminal for Terminal-Bench). Non-official scaffolds → matches_canonical=false."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""BrowseComp (1266)""}",True
+browsecomp_cm,BrowseComp (w/ Context Manage),Agentic,accuracy (%),,https://z.ai/blog/glm-4.7,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Context management: discard-all strategy (not retain-5-turns). Per z.ai/blog/glm-4.7 and GLM-5.1 blog footnote."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""BrowseComp with discard-all context management""}",False
+claw_eval_pass3,Claw Eval (pass^3),Agentic,,,https://huggingface.co/moonshotai/Kimi-K2.6,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""max-tokens-per-step=16384."", ""range"": [0, 100], ""version"": ""Claw Eval v1.1 (pass^3)""}",False
+cybergym,CyberGym,Agentic,% solved,,https://www.anthropic.com/news/claude-opus-4-7,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""CyberGym, agentic cybersecurity capability benchmark. Per Anthropic Opus 4.7 blog (Opus 4.6 score revised from 66.6 to 73.8 with updated harness)."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""CyberGym""}",True
+finance_agent,Finance Agent v1.1,Agentic,% solved,,https://www.anthropic.com/news/claude-opus-4-7,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Finance Agent v1.1, agentic benchmark on financial analysis tasks. Per Anthropic Opus 4.7 blog."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""v1.1""}",True
+gaia,GAIA (text only),Agentic,%,,https://huggingface.co/MiniMaxAI/MiniMax-M2,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per MiniMax M2 model card."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""GAIA (text only)""}",True
+mcpatlas,MCPAtlas Public,Agentic,% correct (pass@1),,https://openai.com/index/introducing-gpt-5-5/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=agentic (scaffold-defined). Preferred = official harness tools (bash/editor for SWE-bench, browser for OSWorld/BrowseComp, official APIs for tau-bench/MCPAtlas/Toolathlon, terminal for Terminal-Bench). Non-official scaffolds → matches_canonical=false."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""MCPAtlas""}",True
+mcpmark,MCPMark,Agentic,,,https://huggingface.co/moonshotai/Kimi-K2.6,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""MCP tool-use benchmark."", ""range"": [0, 100], ""version"": ""MCPMark""}",True
+osworld,OSWorld,Agentic,% success,369.0,https://os-world.github.io/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""tools=agentic (scaffold-defined). Preferred = official harness tools (bash/editor for SWE-bench, browser for OSWorld/BrowseComp, official APIs for tau-bench/MCPAtlas/Toolathlon, terminal for Terminal-Bench). Non-official scaffolds → matches_canonical=false."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""OSWorld (369)""}",True
+tau2_bench_airline,τ²-bench Airline,Agentic,% success,,https://arxiv.org/abs/2506.07982,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""τ²-bench (Barres et al. 2025, arXiv:2506.07982) — dual-control extension of τ-bench: LLM controls BOTH agent and simulated user, both must follow their own policies. airline domain. NOT comparable to τ-bench (Yao et al. 2024) airline cells. Preferred = official harness, pass@1 averaged. tools=agentic (scaffold-defined). Non-official scaffolds → matches_canonical=false."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""τ²-bench (Sierra AI 2025) — airline domain""}",True
+tau2_bench_retail,τ²-bench Retail,Agentic,% success,,https://arxiv.org/abs/2506.07982,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""τ²-bench (Barres et al. 2025, arXiv:2506.07982) — dual-control extension of τ-bench: LLM controls BOTH agent and simulated user, both must follow their own policies. retail domain. NOT comparable to τ-bench (Yao et al. 2024) retail cells. Preferred = official harness, pass@1 averaged. tools=agentic (scaffold-defined). Non-official scaffolds → matches_canonical=false."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""τ²-bench (Sierra AI 2025) — retail domain""}",True
+tau2_bench_telecom,τ²-bench Telecom,Agentic,% success,,https://arxiv.org/abs/2506.07982,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""τ²-bench (Barres et al. 2025, arXiv:2506.07982) — dual-control extension of τ-bench: LLM controls BOTH agent and simulated user, both must follow their own policies. telecom domain. NOT comparable to τ-bench (Yao et al. 2024) telecom cells. Preferred = official harness, pass@1 averaged. tools=agentic (scaffold-defined). Non-official scaffolds → matches_canonical=false."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""τ²-bench (Sierra AI 2025) — telecom domain""}",True
+tau_bench_airline,tau-bench Airline,Agentic,% success,,https://arxiv.org/abs/2406.12045,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Airline domain from tau-bench (Yao et al. 2024). tools=agentic (scaffold-defined). Preferred = official harness tools (bash/editor for SWE-bench, browser for OSWorld/BrowseComp, official APIs for tau-bench/MCPAtlas/Toolathlon, terminal for Terminal-Bench). Non-official scaffolds → matches_canonical=false."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""tau-bench airline""}",True
+tau_bench_retail,Tau-Bench Retail,Agentic,% success,,https://arxiv.org/abs/2406.12045,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=agentic (scaffold-defined). Preferred = official harness tools (bash/editor for SWE-bench, browser for OSWorld/BrowseComp, official APIs for tau-bench/MCPAtlas/Toolathlon, terminal for Terminal-Bench). Non-official scaffolds → matches_canonical=false."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""tau-bench retail""}",True
+tau_bench_telecom,Tau-Bench Telecom,Agentic,% success,,https://arxiv.org/abs/2406.12045,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=agentic (scaffold-defined). Preferred = official harness tools (bash/editor for SWE-bench, browser for OSWorld/BrowseComp, official APIs for tau-bench/MCPAtlas/Toolathlon, terminal for Terminal-Bench). Non-official scaffolds → matches_canonical=false."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""tau-bench telecom""}",False
+terminal_bench,Terminal-Bench 2.0,Agentic,% solved,,https://www.tbench.ai/leaderboard/terminal-bench/2.0,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=agentic (scaffold-defined). Preferred = official harness tools (bash/editor for SWE-bench, browser for OSWorld/BrowseComp, official APIs for tau-bench/MCPAtlas/Toolathlon, terminal for Terminal-Bench). Non-official scaffolds → matches_canonical=false."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""Terminal-Bench (latest)""}",True
+terminal_bench_1,Terminal-Bench 1.0,Agentic,% solved,,https://terminal-bench.com/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=agentic (scaffold-defined). Preferred = official harness tools (bash/editor for SWE-bench, browser for OSWorld/BrowseComp, official APIs for tau-bench/MCPAtlas/Toolathlon, terminal for Terminal-Bench). Non-official scaffolds → matches_canonical=false."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""Terminal-Bench 1.0""}",True
+toolathlon,Toolathlon,Agentic,% correct (pass@1),,https://huggingface.co/moonshotai/Kimi-K2.6,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=agentic (scaffold-defined). Preferred = official harness tools (bash/editor for SWE-bench, browser for OSWorld/BrowseComp, official APIs for tau-bench/MCPAtlas/Toolathlon, terminal for Terminal-Bench). Non-official scaffolds → matches_canonical=false."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""Toolathlon""}",True
+vending_bench_2,Vending-Bench 2,Agentic,,,https://andonlabs.com/evals/vending-bench-2,"{""higher_is_better"": true, ""metric_type"": ""dollars"", ""multimodal_input"": false, ""notes"": ""Net worth (mean) over simulated year of vending machine business operation."", ""range"": [0, 100000], ""version"": ""Vending-Bench 2 (long-horizon planning)""}",True
+swe_evo,SWE-Evo,Agentic Coding,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""code execution"", ""version"": ""SWE-Evo""}",False
+browsecomp_zh,BrowseComp-ZH,Agentic search,,,https://moonshotai.github.io/Kimi-K2/thinking.html,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Chinese version of BrowseComp."", ""range"": [0, 100], ""version"": ""BrowseComp-ZH (Chinese)""}",True
+frames,Frames,Agentic search,,,https://moonshotai.github.io/Kimi-K2/thinking.html,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Search/QA benchmark."", ""range"": [0, 100], ""version"": ""Frames""}",True
+covost2,CoVoST2 (21 lang),Audio,,,https://github.com/facebookresearch/covost,"{""higher_is_better"": true, ""metric_type"": ""bleu"", ""multimodal_input"": true, ""notes"": ""Automatic speech translation across 21 languages (BLEU score)."", ""range"": [0, 100], ""version"": ""CoVoST2 21-language speech translation (BLEU)""}",False
+fleurs,FLEURS,Audio,,,https://huggingface.co/blog/gemma4,"{""higher_is_better"": false, ""metric_type"": ""wer"", ""multimodal_input"": true, ""notes"": ""Speech recognition WER. Lower is better."", ""range"": [0, 1], ""version"": ""FLEURS speech recognition (WER, lower is better)""}",False
+bullshit_pushback,Bullshit-Bench (Clear Pushback),Behavior,% clear pushback,55.0,https://github.com/petergpt/bullshit-benchmark,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""Bullshit-pushback (55)""}",True
+alpacaeval_2,AlpacaEval 2.0 (LC-winrate),Chat,%,,https://arxiv.org/abs/2501.12948,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per DS R1 paper."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""AlpacaEval 2.0 (LC-winrate)""}",True
+mt_bench_101,MT-Bench-101,Chat,Score (1-10),,https://github.com/InternLM/InternLM,"{""higher_is_better"": true, ""metric_type"": ""raw"", ""multimodal_input"": false, ""notes"": ""Per InternLM3 GitHub README. MT-Bench-101 scored 1-10."", ""range"": [1, 10], ""tools"": ""none"", ""version"": ""MT-Bench-101 (Score 1-10)""}",False
+wildbench,WildBench,Chat,Raw Score,,https://github.com/InternLM/InternLM,"{""higher_is_better"": true, ""metric_type"": ""raw"", ""multimodal_input"": false, ""notes"": ""Per InternLM3 GitHub README. WildBench raw score."", ""range"": [null, null], ""tools"": ""none"", ""version"": ""WildBench (Raw Score)""}",False
+superchem,Superchem (text-only),Chemistry,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""Superchem (text-only)""}",False
+cluewsc,CLUEWSC,Chinese,%,2574.0,https://huggingface.co/datasets/clue/clue,"{""higher_is_better"": true, ""judge"": ""rule-based"", ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Protocol audit: Chinese Winograd/coreference-style binary classification. Each item contains a Chinese text and two target spans; the model predicts true/false and scoring is exact match/accuracy against the class label. HF clue/clue dataset card reports cluewsc2020 splits with 2,574 test examples, 1,244 train examples, and 304 validation examples. No LLM judge, tools, multimodal input, long context, multi-turn interaction, or repeated sampling is used."", ""range"": [0, 100], ""sampling"": ""single-pass"", ""tools"": ""none"", ""version"": ""CLUEWSC""}",True
+aethercode,AetherCode,Coding,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""AetherCode""}",False
+aider_polyglot_diff,Aider Polyglot (diff mode),Coding,%,,https://openai.com/index/introducing-gpt-5-for-developers/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per OpenAI GPT-5 dev blog. Higher is better"", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""Aider Polyglot (diff)""}",True
+aider_polyglot_whole,Aider Polyglot (whole mode),Coding,%,,https://openai.com/index/gpt-4-1/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per OpenAI GPT-4.1 blog."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""Aider Polyglot (whole mode)""}",True
+artifactsbench,ArtifactsBench,Coding,%,,https://huggingface.co/MiniMaxAI/MiniMax-M2,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per MiniMax M2 model card."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""ArtifactsBench""}",True
+bigcodebench,BigCodeBench,Coding,pass@1 %,1140.0,https://bigcode-bench.github.io/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=agentic (scaffold-defined). Preferred = official harness tools (bash/editor for SWE-bench, browser for OSWorld/BrowseComp, official APIs for tau-bench/MCPAtlas/Toolathlon, terminal for Terminal-Bench). Non-official scaffolds → matches_canonical=false."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""BigCodeBench (1140 full set)""}",True
+bird_sql,Bird-SQL (Dev),Coding,,,https://bird-bench.github.io/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Natural language to executable SQL on Bird-SQL dev split."", ""range"": [0, 100], ""version"": ""Bird-SQL Dev split (NL→SQL)""}",True
+codeforces_avg8,Codeforces (avg@8),Coding,%,,https://arxiv.org/abs/2504.13914,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Seed-Thinking-v1.5 paper."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""Codeforces (avg@8)""}",False
+codeforces_pass8,Codeforces (pass@8),Coding,%,,https://arxiv.org/abs/2504.13914,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Seed-Thinking-v1.5 paper."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""Codeforces (pass@8)""}",False
+codeforces_rating,Codeforces Rating,Coding,Elo rating,,https://codeforces.com/,"{""higher_is_better"": true, ""metric_type"": ""rating"", ""multimodal_input"": false, ""notes"": ""tools=agentic (scaffold-defined). Preferred = official harness tools (bash/editor for SWE-bench, browser for OSWorld/BrowseComp, official APIs for tau-bench/MCPAtlas/Toolathlon, terminal for Terminal-Bench). Non-official scaffolds → matches_canonical=false."", ""range"": null, ""tools"": ""agentic"", ""version"": ""Codeforces live rating""}",True
+codesimpleqa,CodeSimpleQA,Coding,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""CodeSimpleQA""}",False
+expert_swe,Expert-SWE (Internal),Coding,%,,https://openai.com/index/introducing-gpt-5-5/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Internal OpenAI software engineering benchmark."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""Expert-SWE (Internal)""}",False
+humaneval,HumanEval,Coding,pass@1 %,164.0,https://github.com/openai/human-eval,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""HumanEval (Chen et al. 2021)""}",True
+humaneval_plus,HumanEval+,Coding,,,https://arxiv.org/abs/2305.01210,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Hardened HumanEval with extra tests."", ""range"": [0, 100], ""version"": ""HumanEval+ (Liu et al. 2023, expanded test cases)""}",False
+livecodebench,LiveCodeBench,Coding,pass@1 %,1055.0,https://livecodebench.github.io/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=agentic (scaffold-defined). Preferred = official harness tools (bash/editor for SWE-bench, browser for OSWorld/BrowseComp, official APIs for tau-bench/MCPAtlas/Toolathlon, terminal for Terminal-Bench). Non-official scaffolds → matches_canonical=false."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""LiveCodeBench (1055)""}",True
+livecodebench_pro,LiveCodeBench Pro (Elo),Coding,,,https://livecodebench.github.io/pro.html,"{""higher_is_better"": true, ""metric_type"": ""elo"", ""multimodal_input"": false, ""notes"": ""Elo rating against competitive programming pool."", ""range"": [0, 4000], ""version"": ""LiveCodeBench Pro — Codeforces/ICPC/IOI competitive set""}",False
+livecodebench_v5,LiveCodeBench v5,Coding,%,,https://arxiv.org/abs/2504.13914,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Seed-Thinking-v1.5 paper."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""LiveCodeBench v5""}",False
+livecodebench_v6,LiveCodeBench v6,Coding,%,,https://z.ai/blog/glm-4.7,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per GLM-4.7 blog."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""LiveCodeBench v6""}",False
+mbpp_plus,MBPP+,Coding,,,https://cohere.com/research/papers/command-a-technical-report.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Hardened MBPP with extra tests."", ""range"": [0, 100], ""version"": ""MBPP+ (Liu et al. 2024)""}",True
+multi_swe_bench,Multi-SWE-bench,Coding,,,https://arxiv.org/abs/2507.20534,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Multi-language SWE-bench variant."", ""range"": [0, 100], ""version"": ""Multi-SWE-bench""}",True
+multipl_e_avg,MultiPL-E (average),Coding,%,,https://mistral.ai/news/mistral-medium-3,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Mistral Medium 3 blog: 0-shot, average across MultiPL-E languages."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""MultiPL-E (average)""}",True
+ojbench,OJBench,Coding,,,https://arxiv.org/abs/2507.20534,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Online-judge benchmark."", ""range"": [0, 100], ""version"": ""OJBench""}",True
+paperbench,PaperBench,Coding,,,https://arxiv.org/abs/2507.20534,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Code dev from papers."", ""range"": [0, 100], ""version"": ""PaperBench Code-Dev""}",False
+repoqa,RepoQA,Coding,,,https://cohere.com/research/papers/command-a-technical-report.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Repository-level code QA."", ""range"": [0, 100], ""version"": ""RepoQA (32K context, threshold 0.8)""}",True
+scicode,SciCode,Coding,% correct,,https://scicode-bench.github.io/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=agentic (scaffold-defined). Preferred = official harness tools (bash/editor for SWE-bench, browser for OSWorld/BrowseComp, official APIs for tau-bench/MCPAtlas/Toolathlon, terminal for Terminal-Bench). Non-official scaffolds → matches_canonical=false."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""SciCode""}",True
+spreadsheetbench_verified,SpreadsheetBench Verified,Coding,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""code execution"", ""version"": ""SpreadsheetBench Verified""}",False
+swe_bench_multilingual,SWE-bench Multilingual,Coding,% resolved,,https://www.swebench.com/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=agentic (scaffold-defined). Preferred = official harness tools (bash/editor for SWE-bench, browser for OSWorld/BrowseComp, official APIs for tau-bench/MCPAtlas/Toolathlon, terminal for Terminal-Bench). Non-official scaffolds → matches_canonical=false."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""SWE-bench Multilingual""}",True
+swe_bench_multimodal,SWE-bench Multimodal,Coding,% resolved,,https://www.swebench.com/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""tools=agentic. No single standard public scaffold exists for SWE-bench Multimodal; harness choice is model-side (recorded in cell.reported_setting.harness). Any lab-published harness counts as canonical."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""SWE-bench Multimodal""}",False
+swe_bench_pro,SWE-bench Pro,Coding,% resolved,,https://scale.com/leaderboard/swe_bench_pro_public,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=agentic (scaffold-defined). Preferred = official harness tools (bash/editor for SWE-bench, browser for OSWorld/BrowseComp, official APIs for tau-bench/MCPAtlas/Toolathlon, terminal for Terminal-Bench). Non-official scaffolds → matches_canonical=false."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""SWE-bench Pro""}",True
+swe_bench_verified,SWE-bench Verified,Coding,% resolved,500.0,https://www.swebench.com/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""pass@1 over full 500 instances with standard agent scaffold (e.g., bash/editor tools, single attempt). Exclude scores from reduced subsets, custom scaffolds with parallel sampling, or majority-vote/best-of-N. tools=agentic (scaffold-defined). Preferred = official harness tools (bash/editor for SWE-bench, browser for OSWorld/BrowseComp, official APIs for tau-bench/MCPAtlas/Toolathlon, terminal for Terminal-Bench). Non-official scaffolds → matches_canonical=false."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""SWE-bench Verified (500 instances)""}",True
+swelancer,SWE-Lancer IC Diamond,Coding,%,,https://openai.com/index/introducing-gpt-5-3-codex/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""SWE-Lancer IC Diamond benchmark per OpenAI GPT-5.3-Codex blog."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""SWE-Lancer IC Diamond""}",True
+swelancer_freelance_dollars,SWE-Lancer IC SWE Diamond Freelance ($),Coding,dollars,,https://openai.com/index/introducing-gpt-5-for-developers/,"{""higher_is_better"": true, ""metric_type"": ""dollars"", ""multimodal_input"": false, ""notes"": ""Per OpenAI GPT-5 dev blog. Higher is better"", ""range"": [0, 200000], ""tools"": ""agentic"", ""version"": ""SWE-Lancer IC SWE Diamond Freelance ($)""}",True
+terminal_bench_hard,Terminal-Bench Hard,Coding,%,,https://z.ai/blog/glm-4.7,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per GLM-4.7 blog."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""Terminal-Bench Hard""}",True
+aa_intelligence_index,AA Intelligence Index,Composite,index score,,https://artificialanalysis.ai/,"{""higher_is_better"": true, ""metric_type"": ""index"", ""multimodal_input"": false, ""notes"": ""tools varies per sub-eval (composite metric); inherits sub-benchmark canonical."", ""range"": null, ""tools"": ""composite"", ""version"": ""Artificial Analysis Intelligence Index""}",True
+livebench,LiveBench,Composite,overall score,,https://livebench.ai/,"{""higher_is_better"": true, ""metric_type"": ""index"", ""multimodal_input"": false, ""notes"": ""tools varies per sub-eval (composite metric); inherits sub-benchmark canonical."", ""range"": null, ""tools"": ""composite"", ""version"": ""LiveBench (latest)""}",True
+creative_writing_v3,Creative Writing v3 (Elo Normalized),Creative,elo,,https://x.ai/news/grok-4-1,"{""higher_is_better"": true, ""metric_type"": ""elo"", ""multimodal_input"": false, ""notes"": ""Creative Writing v3: 32 prompts × 3 iterations. LLM-judged with rubrics + pairwise battles. Elo normalized. Per xAI Grok 4.1 blog."", ""range"": [1000, 2000], ""tools"": ""none"", ""version"": ""Creative Writing v3 (Elo Normalized)""}",False
+ctf_internal,Capture-the-Flags challenge tasks (Internal),Cyber,%,,https://openai.com/index/introducing-gpt-5-5/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Hardest CTF challenges from system cards plus additional hard challenges."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""Capture-the-Flags challenge tasks (Internal)""}",False
+cybench,Cybench,Cyber,%,40.0,https://arxiv.org/abs/2408.08926,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Public CTF benchmark: 40 challenges from 4 competitions (Zhang et al., 2024). Anthropic evaluated 39/40 (1 skipped due to infra/timing). Score = % of 39 attempted. Pass@30 trials."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""Cybench (public)""}",False
+cybersecurity_ctf,Cybersecurity Capture The Flag Challenges,Cyber,%,,https://openai.com/index/introducing-gpt-5-3-codex/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Cybersecurity CTF benchmark per OpenAI GPT-5.3-Codex blog. Note: distinct from ctf_internal (GPT-5.5 blog uses different problem set)."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""Cybersecurity Capture The Flag Challenges""}",False
+deepconsult,DeepConsult,Deep Research,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""research tools"", ""version"": ""DeepConsult""}",False
+deepresearchbench,DeepResearchBench,Deep Research,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""research tools"", ""version"": ""DeepResearchBench""}",False
+researchrubrics,ResearchRubrics,Deep Research,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""research tools"", ""version"": ""ResearchRubrics""}",False
+chartqapro,ChartQAPro,Document/Chart,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""ChartQAPro""}",False
+dude,DUDE,Document/Chart,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""DUDE""}",False
+ocrbench_v2,OCRBench v2,Document/Chart,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""OCRBench v2""}",False
+eq_bench3,"EQ-Bench3 (Emotional Intelligence, Elo Normalized)",EQ,elo,,https://x.ai/news/grok-4-1,"{""higher_is_better"": true, ""metric_type"": ""elo"", ""multimodal_input"": false, ""notes"": ""EQ-Bench3: 45 roleplay scenarios × 3 turns. LLM-judged with rubrics + pairwise battles. Elo normalized. Per xAI Grok 4.1 blog."", ""range"": [1000, 2000], ""tools"": ""none"", ""version"": ""EQ-Bench3 (Emotional Intelligence, Elo Normalized)""}",False
+gdpval_diamond,GDPVal-Diamond,Economic,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""GDPVal-Diamond""}",False
+xpert_bench,XPertBench,Economic,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""XPertBench""}",False
+facts_benchmark,FACTS Benchmark Suite,Factuality,,,https://deepmind.google/models/gemini/flash/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Factuality across grounding, parametric, search, and multimodal."", ""range"": [0, 100], ""version"": ""FACTS Benchmark Suite (grounding/parametric/search/MM)""}",False
+facts_grounding,FACTS Grounding,Factuality,,1719.0,https://arxiv.org/abs/2501.03200,"{""higher_is_better"": true, ""judge"": ""LLM judge ensemble (Gemini 1.5 Pro, GPT-4o, Claude 3.5 Sonnet)"", ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""FACTS Grounding evaluates whether long-form model responses are factually accurate and grounded in a provided context document. The paper reports 1,719 total examples split into Open N=860 and Blind N=859. Each prompt includes a user request and a full document, with context up to 32k tokens. Models generate long-form responses; scoring uses prompted LLM judges in two phases: responses are first disqualified if they do not fulfill the user request, then judged accurate if fully grounded in the document. The factuality score aggregates three judge models (Gemini 1.5 Pro, GPT-4o, Claude 3.5 Sonnet) to mitigate judge bias."", ""range"": [0, 100], ""sampling"": ""single-pass model response; scored by three prompted judge models plus eligibility filter"", ""tools"": ""none"", ""version"": ""FACTS Grounding long-context factuality benchmark""}",True
+truthfulqa,TruthfulQA,Factuality,,,https://arxiv.org/abs/2501.00656,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Truthfulness benchmark."", ""range"": [0, 100], ""version"": ""TruthfulQA""}",True
+ib_modeling,Investment Banking Modeling Tasks (Internal),Finance,%,,https://openai.com/index/introducing-gpt-5-5/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Internal OpenAI IB modeling benchmark."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""Investment Banking Modeling Tasks (Internal)""}",False
+phibench,PhiBench (Microsoft Internal),General,,,https://arxiv.org/abs/2412.08905,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Microsoft Phi team internal eval."", ""range"": [0, 100], ""version"": ""PhiBench 2.21 (Microsoft internal)""}",False
+factscore,FActScore (hallucination rate),Hallucination,%,500.0,https://github.com/shmsw25/FActScore,"{""higher_is_better"": false, ""judge"": ""retrieval+LLM judge/factuality estimator"", ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Official FActScore evaluates long-form biography generation for factual precision. The README defines two prompt-entity sets: 183 labeled entities for human-annotated sections and 500 unlabeled entities for broad model evaluation; use the 500-entity unlabeled set as the scored benchmark count. Each model generates a biography for a person entity, then FActScore decomposes the generation into atomic facts and verifies each fact against a Wikipedia knowledge source using retrieval+ChatGPT or retrieval+LLAMA+NP. The official README estimates API cost at about $1 per 100 sentences and reports that 6,500 generations from 13 LMs would have cost $26K if evaluated by humans. Some provider tables report hallucination rate (lower is better) rather than FActScore factual precision (higher is better); preserve source-level score semantics in score-cell notes."", ""range"": [0, 100], ""sampling"": ""single-pass generation; each biography is decomposed into atomic facts and verified against Wikipedia"", ""tools"": ""none"", ""version"": ""FActScore unlabeled 500-entity biography set; benchmark tables may use either FActScore or hallucination rate""}",True
+longfact_concepts,LongFact-Concepts (hallucination rate),Hallucination,%,,https://openai.com/index/introducing-gpt-5-for-developers/,"{""higher_is_better"": false, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per OpenAI GPT-5 dev blog. LOWER IS BETTER."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""LongFact-Concepts (hallucination rate)""}",True
+longfact_objects,LongFact-Objects (hallucination rate),Hallucination,%,,https://openai.com/index/introducing-gpt-5-for-developers/,"{""higher_is_better"": false, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per OpenAI GPT-5 dev blog. LOWER IS BETTER."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""LongFact-Objects (hallucination rate)""}",True
+healthbench_consensus,HealthBench Consensus,Health,,,https://arxiv.org/abs/2508.10925,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Consensus subset of HealthBench."", ""range"": [0, 100], ""version"": ""HealthBench Consensus""}",False
+healthbench_hard,HealthBench Hard,Health,,,https://arxiv.org/abs/2508.10925,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Harder subset of HealthBench."", ""range"": [0, 100], ""version"": ""HealthBench Hard subset""}",False
+chatbot_arena_elo,Chatbot Arena Elo,Human Preference,Elo rating,,https://lmarena.ai/,"{""higher_is_better"": true, ""metric_type"": ""elo"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": null, ""tools"": ""none"", ""version"": ""LMArena (Chatbot Arena) live Elo""}",True
+arena_hard,Arena-Hard Auto,Instruction Following,% win rate,500.0,https://lmarena.ai/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""Arena-Hard-Auto""}",True
+collie,COLLIE,Instruction Following,%,2080.0,https://arxiv.org/abs/2307.08689,"{""higher_is_better"": true, ""judge"": ""rule-based"", ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Protocol audit: constrained text generation benchmark. Each item renders a natural-language instruction from a formal COLLIE constraint structure; the model outputs free-form text, and scoring checks whether the generated text satisfies the target constraint. The COLLIE paper reports COLLIE-v1 has 2,080 instances across 13 constraint structures. The official repo documents evaluation via the constraint checker, so scoring is rule-based/programmatic rather than LLM-judged. BenchPress cells from OpenAI/Doubao reports use pass@1/single-response settings. No tools, multimodal input, long context, or multi-turn interaction is used."", ""range"": [0, 100], ""sampling"": ""pass@1; single response"", ""tools"": ""none"", ""version"": ""COLLIE""}",True
+ifbench,IFBench,Instruction Following,% correct,,https://arxiv.org/abs/2502.09980,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""IFBench""}",True
+ifeval,IFEval,Instruction Following,% correct (prompt strict),541.0,https://arxiv.org/abs/2311.07911,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""IFEval prompt-strict (541)""}",True
+internal_api_if_hard,Internal API IF Hard,Instruction Following,%,,https://openai.com/index/introducing-gpt-5-for-developers/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per OpenAI GPT-5 dev blog. Higher is better"", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""Internal API IF Hard""}",True
+inverse_ifeval,Inverse IFEval,Instruction Following,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""Inverse IFEval""}",False
+mars_bench,MARS-Bench,Instruction Following,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""MARS-Bench""}",False
+multi_if,Multi-IF,Instruction Following,%,,https://openai.com/index/gpt-4-1/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per OpenAI GPT-4.1 blog."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""Multi-IF""}",True
+multichallenge,MultiChallenge,Instruction Following,%,,https://openai.com/index/gpt-4-1/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per OpenAI GPT-4.1 blog."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""MultiChallenge""}",True
+multichallenge_o3mini_grader,MultiChallenge (o3-mini grader),Instruction Following,%,,https://openai.com/index/introducing-gpt-5-for-developers/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per OpenAI GPT-5 dev blog. Higher is better"", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""Scale MultiChallenge""}",True
+infobench,InFoBench,Instruction following,,,https://cohere.com/research/papers/command-a-technical-report.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Instruction following benchmark."", ""range"": [0, 100], ""version"": ""InFoBench""}",True
+c_eval,C-Eval (Chinese),Knowledge,%,12342.0,https://huggingface.co/datasets/ceval/ceval-exam,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""HF dataset card reports 13,948 total questions across splits; the test split has 12,342 scored multiple-choice questions across 52 subjects."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""C-Eval (Chinese)""}",True
+chinese_simpleqa,Chinese-SimpleQA,Knowledge,%,3000.0,https://huggingface.co/datasets/OpenStellarTeam/Chinese-SimpleQA,"{""higher_is_better"": true, ""judge"": ""LLM grader"", ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Protocol audit: short Chinese factual QA. Each item asks a short-answer factual question; model output is judged for correctness against reference answers. HF dataset card reports 3,000 questions across 6 topics and says grading is run via existing LLMs. No tools, multimodal input, long context, multi-turn interaction, or repeated sampling is specified."", ""range"": [0, 100], ""sampling"": ""single-pass; no repeated sampling specified"", ""tools"": ""none"", ""version"": ""Chinese-SimpleQA""}",True
+cmmlu,CMMLU (Chinese),Knowledge,%,,https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per DeepSeek V4-Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""CMMLU (Chinese)""}",False
+encyclo_k,Encyclo-K,Knowledge,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""Encyclo-K""}",False
+gdpval_aa_elo,GDPval (Artificial Analysis ELO),Knowledge,score,,https://artificialanalysis.ai/evaluations/gdpval-aa,"{""higher_is_better"": true, ""metric_type"": ""index"", ""multimodal_input"": false, ""notes"": ""tools varies per sub-eval (composite metric); inherits sub-benchmark canonical. Renamed from gdpval_aa for clarity (ELO from Artificial Analysis)."", ""range"": null, ""tools"": ""composite"", ""version"": ""GDPval (Artificial Analysis)""}",True
+global_mmlu_lite,Global MMLU Lite,Knowledge,,7200.0,https://huggingface.co/datasets/CohereForAI/Global-MMLU-Lite,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Multilingual MMLU subset by Cohere. HF dataset card reports 18 languages with 400 test examples each. Distinct from MMLU (5-shot 14k EN) and MMMLU (multilingual MMLU full)."", ""range"": [0, 100], ""version"": ""Global MMLU Lite (multilingual MMLU subset, Cohere)""}",False
+healthbench,HealthBench,Knowledge,%,,https://huggingface.co/moonshotai/Kimi-K2-Thinking,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Kimi K2-Thinking model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""HealthBench""}",True
+lpfqa,LPFQA,Knowledge,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""LPFQA""}",False
+mmlu,MMLU,Knowledge,% correct,14042.0,https://arxiv.org/abs/2009.03300,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""MMLU (5-shot, 14042 questions)""}",False
+mmlu_pro,MMLU-Pro,Knowledge,% correct,12032.0,https://arxiv.org/abs/2406.01574,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""MMLU-Pro""}",True
+mmlu_redux,MMLU-Redux,Knowledge,,,https://arxiv.org/abs/2406.04127,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Cleaned version of MMLU (Gema et al. 2024). 5-shot."", ""range"": [0, 100], ""version"": ""MMLU-Redux (5-shot)""}",False
+mmmlu,MMMLU,Knowledge,% correct,258090.0,https://huggingface.co/datasets/openai/MMMLU,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). HF dataset contains 14 translated MMLU test CSVs; row count across test CSVs is 258,090. If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""MMMLU (multilingual MMLU)""}",True
+simpleqa,SimpleQA,Knowledge,% correct,4326.0,https://openai.com/index/introducing-simpleqa/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""SimpleQA (OpenAI 4326 questions)""}",True
+simpleqa_verified,SimpleQA-Verified,Knowledge,% correct (pass@1),,https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""SimpleQA-Verified""}",True
+aa_lcr,AA Long Context Reasoning,Long Context,% correct,,https://artificialanalysis.ai/evaluations/artificial-analysis-long-context-reasoning,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""Artificial Analysis Long Context Reasoning""}",True
+browsecomp_long_context_128k,BrowseComp Long Context 128k,Long Context,%,,https://openai.com/index/gpt-5-1-for-developers/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""BrowseComp Long Context 128k subset, per OpenAI GPT-5.1 dev blog."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""BrowseComp Long Context 128k""}",True
+browsecomp_long_context_256k,BrowseComp Long Context 256k,Long Context,,,,"{""judge"": ""rule-based"", ""notes"": ""Per OpenAI GPT-5 developer blog https://openai.com/index/introducing-gpt-5-for-developers/""}",False
+cl_bench,CL-Bench,Long Context,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""CL-Bench""}",False
+corpusqa_1m,CorpusQA 1M,Long Context,%,,https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per DeepSeek V4-Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""CorpusQA 1M""}",False
+flenqa_3k,FlenQA (3K-token),Long Context,,,https://arxiv.org/abs/2402.14848,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Long-context QA at 3K tokens."", ""range"": [0, 100], ""version"": ""FlenQA 3K-token subset""}",False
+graphwalks_bfs_0k_128k,GraphWalks BFS 0-128K,Long Context,%,,https://openai.com/index/introducing-gpt-5-4/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per OpenAI GPT-5.4 blog."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""GraphWalks BFS 0-128K""}",True
+graphwalks_bfs_128k_plus,GraphWalks BFS >128k,Long Context,%,,https://openai.com/index/gpt-4-1/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per OpenAI GPT-4.1 blog."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""GraphWalks BFS >128k""}",False
+graphwalks_bfs_256k_1m,GraphWalks BFS 256K-1M,Long Context,% f1 (avg 256K-1M),,https://openai.com/index/introducing-gpt-5-5/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""GraphWalks BFS 256K-1M""}",False
+graphwalks_parents_0k_128k,GraphWalks parents 0-128K,Long Context,%,,https://openai.com/index/introducing-gpt-5-4/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per OpenAI GPT-5.4 blog."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""GraphWalks parents 0-128K""}",True
+graphwalks_parents_128k_plus,GraphWalks parents >128k,Long Context,%,,https://openai.com/index/gpt-4-1/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per OpenAI GPT-4.1 blog."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""GraphWalks parents >128k""}",False
+graphwalks_parents_256k_1m,GraphWalks parents 256K-1M,Long Context,%,,https://openai.com/index/introducing-gpt-5-4/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per OpenAI GPT-5.4 blog."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""GraphWalks parents 256K-1M""}",False
+loft_128k,LOFT (128k),Long Context,%,,https://x.ai/news/grok-3,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per xAI Grok 3 blog."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""LOFT (128k)""}",False
+longbench_v2,LongBench-V2,Long Context,%,,https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per DeepSeek V4-Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""LongBench-V2""}",True
+mrcr_v2,MRCR v2,Long Context,% correct,,https://arxiv.org/abs/2407.05530,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""MRCR v2""}",True
+mrcr_v2_2needle_128k,"OpenAI MRCR v2 (2 needle, 128k)",Long Context,%,,https://openai.com/index/gpt-4-1/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per OpenAI GPT-4.1 blog."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""OpenAI MRCR v2 (2 needle, 128k)""}",True
+mrcr_v2_2needle_1m,"OpenAI MRCR v2 (2 needle, 1M)",Long Context,%,,https://openai.com/index/gpt-4-1/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per OpenAI GPT-4.1 blog."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""OpenAI MRCR v2 (2 needle, 1M)""}",False
+mrcr_v2_2needle_256k,"OpenAI MRCR v2 (2-needle, 256k)",Long Context,,,,"{""judge"": ""rule-based"", ""notes"": ""Per OpenAI GPT-5 developer blog https://openai.com/index/introducing-gpt-5-for-developers/""}",False
+mrcr_v2_8needle,OpenAI MRCR v2 (8-needle),Long Context,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""OpenAI MRCR v2 (8-needle)""}",True
+ruler_128k,RULER 128K,Long Context,%,,https://mistral.ai/news/mistral-medium-3,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Mistral Medium 3 blog: RULER long-context benchmark @ 128K tokens."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""RULER 128K""}",False
+ruler_32k,RULER 32K,Long Context,%,,https://mistral.ai/news/mistral-medium-3,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Mistral Medium 3 blog: RULER long-context benchmark @ 32K tokens."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""RULER 32K""}",False
+mrcr_v1,MRCR v1,Long-context,,,https://storage.googleapis.com/deepmind-media/Model-Cards/Gemini-2-0-Flash-Model-Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Multi-Round Coreference Resolution v1 at 1M context. Distinct from MRCR v2 8-needle."", ""range"": [0, 100], ""version"": ""MRCR v1""}",True
+aime_2024,AIME 2024,Math,% correct (pass@1),30.0,https://artofproblemsolving.com/wiki/index.php/2024_AIME,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""AIME-2024-I+II (30 problems)""}",True
+aime_2025,AIME 2025,Math,% correct (pass@1),30.0,https://artofproblemsolving.com/wiki/index.php/2025_AIME,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""AIME-2025-I+II (30 problems)""}",True
+aime_2026,AIME 2026,Math,% correct (pass@1),30.0,https://huggingface.co/datasets/MathArena/aime_2026_I,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""AIME-2026-I+II (30 problems)""}",True
+apex_shortlist,Apex Shortlist,Math,% correct (pass@1),,https://matharena.ai/apex/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""Apex shortlist""}",False
+beyond_aime,Beyond AIME,Math,%,100.0,https://huggingface.co/datasets/ByteDance-Seed/BeyondAIME,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""HF dataset card reports one test split with 100 problems; answers are positive integers with automated exact verification. Per Seed-Thinking-v1.5 paper."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""Beyond AIME""}",True
+brumo_2025,BRUMO 2025,Math,% correct (pass@1),30.0,https://huggingface.co/datasets/MathArena/brumo_2025,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""sampling"": ""samples=4"", ""tools"": ""none"", ""version"": ""BRUMO 2025""}",True
+cmimc_2025,CMIMC 2025,Math,% correct (pass@1),40.0,https://huggingface.co/datasets/MathArena/cmimc_2025,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""sampling"": ""samples=4"", ""tools"": ""none"", ""version"": ""CMIMC 2025""}",True
+cnmo_2024,CNMO 2024,Math,%,6.0,https://www.cms.org.cn/Home/comp/comp_details/id/1253.html,"{""higher_is_better"": true, ""judge"": ""rule-based"", ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Protocol audit: Chinese National High School Mathematics Olympiad 2024 finals, pure text olympiad math. The official CMS page identifies the 2024 national final / 40th winter camp; the standard CMO format is two days with 3 problems per day (format source: https://zh.wikipedia.org/wiki/中国数学奥林匹克), so the scored set has 6 proof-style math problems. DeepSeek-R1-0528 reports CNMO 2024 as Pass@1 and states that benchmarks requiring sampling use temperature 0.6, top-p 0.95, and 16 responses per query to estimate pass@1. Scoring is rule-based/manual exact mathematical correctness; no LLM judge, tools, multimodal input, long context, or multi-turn interaction."", ""range"": [0, 100], ""sampling"": ""samples=16"", ""tools"": ""none"", ""version"": ""CNMO 2024""}",True
+dynamath,DynaMath,Math,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""DynaMath""}",False
+frontiermath,FrontierMath,Math,% correct T1-3,300.0,https://epoch.ai/benchmarks/frontiermath,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""FrontierMath Tier 1-3 (300)""}",True
+frontiermath_tier4,FrontierMath Tier 4,Math,%,,https://openai.com/index/introducing-gpt-5-5/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Hardest tier (Tier 4) of FrontierMath. More difficult than Tier 1-3."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""FrontierMath Tier 4""}",True
+gsm8k,GSM8K,Math,% correct,1319.0,https://arxiv.org/abs/2110.14168,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""GSM8K (test, 1319 problems)""}",True
+hiddenmath,HiddenMath,Math,,,https://storage.googleapis.com/deepmind-media/Model-Cards/Gemini-2-0-Flash-Model-Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Google internal held-out math benchmark, AIME/AMC-style, not leaked online."", ""range"": [0, 100], ""version"": ""HiddenMath (held-out AIME/AMC-like, Google internal)""}",False
+hmmt_feb_2025,HMMT Feb 2025,Math,%,30.0,https://huggingface.co/datasets/MathArena/hmmt_feb_2025,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""MathArena dataset has 30 questions; MathArena evaluates each model 4 times per problem."", ""range"": [0, 100], ""sampling"": ""samples=4"", ""tools"": ""none"", ""version"": ""HMMT Feb 2025""}",True
+hmmt_feb_2026,HMMT Feb 2026,Math,% correct (pass@1),33.0,https://huggingface.co/datasets/MathArena/hmmt_feb_2026,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""sampling"": ""samples=4"", ""tools"": ""none"", ""version"": ""HMMT Feb 2026""}",True
+hmmt_nov_2025,HMMT Nov 2025,Math,% correct,30.0,https://huggingface.co/datasets/MathArena/hmmt_nov_2025,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""sampling"": ""samples=4"", ""tools"": ""none"", ""version"": ""HMMT Nov 2025""}",True
+imo_2025,IMO 2025,Math,% of 42 points,6.0,https://matharena.ai/imo/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""IMO 2025""}",False
+imo_answerbench,IMO-AnswerBench,Math,,,https://moonshotai.github.io/Kimi-K2/thinking.html,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""avg@8."", ""range"": [0, 100], ""version"": ""IMO-AnswerBench""}",True
+math,MATH,Math,,12500.0,https://github.com/hendrycks/math,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Full MATH benchmark (algebra, geometry, pre-calculus, etc). Distinct from MATH-500 subset."", ""range"": [0, 100], ""version"": ""MATH (Hendrycks et al. 2021, full set)""}",True
+math_500,MATH-500,Math,% correct,500.0,https://arxiv.org/abs/2103.03874,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""MATH-500 subset (Hendrycks)""}",True
+matharena_apex_2025,MathArena Apex 2025,Math,% correct,,https://matharena.ai/apex/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""MathArena Apex 2025""}",True
+mathcanvas,MathCanvas,Math,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""MathCanvas""}",False
+mathkangaroo,MathKangaroo,Math,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""MathKangaroo""}",False
+mathvision,MathVision,Math,% correct,,https://mathvision-cuhk.github.io/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""MathVision""}",True
+mgsm,MGSM,Math,%,,https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per DeepSeek V4-Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""MGSM""}",True
+mt_aime_2024,MT-AIME2024,Math,,,https://arxiv.org/abs/2505.09388,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Multilingual AIME 2024 across 55 languages."", ""range"": [0, 100], ""version"": ""MT-AIME2024 (multilingual AIME 2024, 55 languages, Son et al. 2025)""}",True
+omnimath,OmniMath,Math,,,https://arxiv.org/abs/2410.07985,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Olympiad-level math benchmark."", ""range"": [0, 100], ""version"": ""OmniMath""}",False
+smt_2025,SMT 2025,Math,% correct (pass@1),53.0,https://huggingface.co/datasets/MathArena/smt_2025,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""sampling"": ""samples=4"", ""tools"": ""none"", ""version"": ""SMT 2025""}",True
+usamo_2025,USAMO 2025,Math,% of 42 points,6.0,https://huggingface.co/datasets/MathArena/usamo_2025,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""USAMO 2025""}",True
+usamo_2026,USAMO 2026,Math,% of 42 points,6.0,https://matharena.ai/usamo/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""USAMO 2026""}",False
+mathvista,MathVista,Math/Vision,%,,https://openai.com/index/gpt-4-1/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per OpenAI GPT-4.1 blog."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""MathVista""}",True
+medxpertqa_mm,MedXpertQA MM,Medical,,,https://huggingface.co/blog/gemma4,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Medical visual QA."", ""range"": [0, 100], ""version"": ""MedXpertQA Multimodal""}",False
+medxpertqa_text,MedXpertQA (Text),Medical,,,,"{""higher_is_better"": true, ""judge"": ""gpt-oss-120b"", ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Meta MSL eval methodology: 2,450 prompts spanning medical specialties; 10 answer choices; graded with gpt-oss-120b. Source: https://ai.meta.com/blog/introducing-muse-spark-msl/"", ""range"": [0, 100], ""version"": ""MedXpertQA Text (2,450 prompts, 10-choice A–J)""}",False
+disco_x,Disco-X,Multilingual,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""Disco-X""}",False
+multilingual_mmlu,Multilingual MMLU,Multilingual,,,https://huggingface.co/microsoft/Phi-4-mini-instruct,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""5-shot MMLU across multiple languages."", ""range"": [0, 100], ""version"": ""Multilingual MMLU (5-shot)""}",False
+ntrex,NTREX,Multilingual,,,https://cohere.com/research/papers/command-a-technical-report.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Machine translation COMET-20 score."", ""range"": [0, 100], ""version"": ""NTREX (COMET-20)""}",False
+ai2d,AI2D,Multimodal,%,,https://mistral.ai/news/mistral-medium-3,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Mistral Medium 3 blog: AI2 Diagram understanding benchmark, 0-shot."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""AI2D""}",False
+babyvision,BabyVision,Multimodal,,,https://huggingface.co/moonshotai/Kimi-K2.6,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Vision benchmark."", ""range"": [0, 100], ""version"": ""BabyVision""}",True
+chartqa,ChartQA,Multimodal,%,,https://mistral.ai/news/mistral-medium-3,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Mistral Medium 3 blog: Chart visual question answering, 0-shot."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""ChartQA""}",False
+charxiv_reasoning,CharXiv Reasoning,Multimodal,% correct (no tools),,https://charxiv.github.io/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""CharXiv Reasoning""}",True
+docvqa,DocVQA,Multimodal,%,,https://mistral.ai/news/mistral-medium-3,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Mistral Medium 3 blog: Document visual question answering, 0-shot."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""DocVQA""}",False
+mmmu,MMMU,Multimodal,% correct,900.0,https://mmmu-benchmark.github.io/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""MMMU validation (900 questions)""}",True
+mmmu_pro,MMMU-Pro,Multimodal,% correct,,https://arxiv.org/abs/2409.02813,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""MMMU Pro""}",True
+ocrbench,OCRBench,Multimodal,,,https://huggingface.co/moonshotai/Kimi-K2.5,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""OCR benchmark."", ""range"": [0, 100], ""version"": ""OCRBench""}",False
+screenspot_pro,ScreenSpot-Pro,Multimodal,,,https://deepmind.google/models/gemini/flash/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Screen understanding benchmark."", ""range"": [0, 100], ""version"": ""ScreenSpot-Pro (screen understanding)""}",True
+vibe_eval,Vibe-Eval,Multimodal,,,https://github.com/reka-ai/reka-vibe-eval,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Vibe-Eval (Reka) image understanding benchmark."", ""range"": [0, 100], ""version"": ""Vibe-Eval (Reka)""}",True
+video_mme,Video-MME,Multimodal,,,https://video-mme.github.io/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Video-MME video QA benchmark. Distinct from Video-MMMU (subject-knowledge from videos)."", ""range"": [0, 100], ""version"": ""Video-MME (audio + visual + subtitles)""}",True
+mathvista_mini,MathVista (mini),Multimodal Math,,,https://huggingface.co/moonshotai/Kimi-K2.5,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""avg@3."", ""range"": [0, 100], ""version"": ""MathVista mini""}",False
+gdpval_oai_woe,GDPval (OpenAI wins-or-ties),Office,%,,https://openai.com/index/introducing-gpt-5-5/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""OpenAI GDPval head-to-head wins or ties %, baseline against reference. Single-source: OpenAI GPT-5.5 blog."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""GDPval (OpenAI wins-or-ties)""}",False
+officeqa,OfficeQA,Office,%,,https://openai.com/index/introducing-gpt-5-4/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""OfficeQA productivity benchmark (different from OfficeQA Pro). Per OpenAI GPT-5.4 blog."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""OfficeQA""}",False
+officeqa_pro,OfficeQA Pro,Office,%,,https://openai.com/index/introducing-gpt-5-5/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Office productivity QA benchmark."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""OfficeQA Pro""}",False
+phybench,Phybench,Physics,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""Phybench""}",False
+popqa,PopQA,QA,,,https://arxiv.org/abs/2501.00656,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Long-tail factuality."", ""range"": [0, 100], ""version"": ""PopQA""}",True
+tob_complex_workflows,ToB-ComplexWorkflows,Real-world,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""ToB-ComplexWorkflows""}",False
+tob_compositional_tasks,ToB-CompositionalTasks,Real-world,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""ToB-CompositionalTasks""}",False
+tob_information_extraction,ToB-InformationExtraction,Real-world,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""ToB-InformationExtraction""}",False
+tob_k12_education,ToB-K12Education,Real-world,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""ToB-K12Education""}",False
+tob_referenceqa,ToB-ReferenceQ&A,Real-world,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""ToB-ReferenceQ&A""}",False
+tob_text_classification,ToB-TextClassification,Real-world,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""ToB-TextClassification""}",False
+world_travel_text,WorldTravel (TEXT),Real-world,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""WorldTravel (TEXT)""}",False
+world_travel_vlm,WorldTravel (VLM),Real-world,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""WorldTravel (VLM)""}",False
+arc_agi_1,ARC-AGI-1,Reasoning,% correct,400.0,https://arcprize.org/arc-agi/1/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""ARC-AGI-1 (semi-private 400)""}",True
+arc_agi_2,ARC-AGI-2,Reasoning,% correct,400.0,https://arcprize.org/arc-agi/2/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""ARC-AGI-2 (semi-private 400)""}",True
+arc_challenge,ARC Challenge,Reasoning,,,https://arxiv.org/abs/1803.05457,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""AI2 ARC Challenge subset."", ""range"": [0, 100], ""version"": ""ARC Challenge (10-shot)""}",False
+babe,BABE,Reasoning,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""BABE""}",False
+bigbench_extra_hard,BigBench Extra Hard,Reasoning,,,https://huggingface.co/blog/gemma4,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Hard subset of BIG-Bench."", ""range"": [0, 100], ""version"": ""BigBench Extra Hard""}",False
+bigbench_hard,BigBench Hard (BBH),Reasoning,,,https://arxiv.org/abs/2210.09261,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""BIG-Bench Hard subset. Distinct from bigbench_extra_hard."", ""range"": [0, 100], ""version"": ""BBH 0-shot CoT""}",True
+der2_bench,DeR2 Bench,Reasoning,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""DeR2 Bench""}",False
+drop,DROP,Reasoning,%,9536.0,https://huggingface.co/datasets/EleutherAI/drop,"{""higher_is_better"": true, ""judge"": ""rule-based"", ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""DROP is passage-question reading comprehension requiring discrete reasoning. HF EleutherAI/drop reports 77,409 train rows and 9,536 validation rows; use validation as the scored evaluation split. HF ucinlp/drop reports 9,535 validation rows, so the one-row discrepancy is noted and EleutherAI/drop is used because it matches common lm-eval-style benchmark packaging. The official paper describes DROP as a 96k-question benchmark. Official evaluation uses normalized exact match and F1 over number/date/span answers; no LLM judge or tool use."", ""range"": [0, 100], ""sampling"": ""single-pass"", ""tools"": ""none"", ""version"": ""DROP validation split""}",True
+global_piqa,Global PIQA,Reasoning,,,https://deepmind.google/models/gemini/flash/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Multilingual commonsense reasoning."", ""range"": [0, 100], ""version"": ""Global PIQA (commonsense across 100 languages/cultures)""}",True
+hellaswag,HellaSwag,Reasoning,%,,https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per DeepSeek V4-Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""HellaSwag""}",False
+hle,HLE (Humanity's Last Exam),Reasoning,% correct,2500.0,https://lastexam.ai/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""Humanity's Last Exam (2500)""}",True
+korbench,KORBench,Reasoning,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""KORBench""}",False
+procbench,ProcBench,Reasoning,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""ProcBench""}",False
+simplebench,SimpleBench,Reasoning,% correct,1000.0,https://simple-bench.com/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""SimpleBench (1000)""}",False
+hle_tools,HLE (w/ tools),Reasoning & Knowledge,accuracy (%),,https://huggingface.co/moonshotai/Kimi-K2.5,"{""metric"": ""accuracy (%)"", ""notes"": ""Tool-augmented evaluation (search, code execution, web browsing enabled)"", ""pass_at_k"": ""pass@1"", ""version"": ""Full text+image set with tools""}",True
+zerobench_tools,ZeroBench (w/ tools),Reasoning & Knowledge,accuracy (%),,https://huggingface.co/moonshotai/Kimi-K2.5,"{""metric"": ""accuracy (%)"", ""notes"": ""Tool-augmented evaluation"", ""pass_at_k"": ""pass@1"", ""version"": ""ZeroBench with tools""}",False
+nl2repo_bench,NL2Repo-Bench,Repository Code,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""code execution"", ""version"": ""NL2Repo-Bench""}",True
+nl2repo_pass1,NL2Repo (Pass@1),Repository Code,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""code execution"", ""version"": ""NL2Repo (Pass@1)""}",False
+safety,Safety (OLMES suite),Safety,,,https://arxiv.org/abs/2501.00656,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Allen AI internal safety eval suite."", ""range"": [0, 100], ""version"": ""OLMES safety suite""}",True
+bixbench,BixBench,Science,%,,https://openai.com/index/introducing-gpt-5-5/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Biology/Chemistry expert-level benchmark."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""BixBench""}",False
+critpt,CritPt,Science,% correct,70.0,https://huggingface.co/datasets/CritPt-Benchmark/CritPt,"{""higher_is_better"": true, ""judge"": ""automated rule-based scoring server"", ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Protocol audit: frontier research-level physics benchmark. The public test set has 70 challenges; the broader benchmark has 71 composite research challenges plus an example and 190 checkpoint tasks. Each challenge is a text-only, unpublished physics research problem spanning modern physics subfields, with guess-resistant, machine-verifiable answers. Primary leaderboard metric is average challenge accuracy over 5 runs x 70 test challenges. The official pipeline submits complete batches to an automated grading server customized for advanced physics-specific output formats. Canonical BenchPress setting is no tools; with-code/web-tool variants are non-canonical. The official repo's no-tool config disables Python and web search; reasoning-model examples use large reasoning budgets (e.g. 27k reasoning tokens)."", ""range"": [0, 100], ""sampling"": ""trials=5"", ""tools"": ""none"", ""version"": ""CRITPT""}",True
+frontier_science_research,Frontier Science Research,Science,%,,https://openai.com/index/introducing-gpt-5-4/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Frontier-level science research benchmark. Per OpenAI GPT-5.4 blog."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""Frontier Science Research""}",False
+frontiersci_olympiad,FrontierSci-olympiad,Science,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""FrontierSci-olympiad""}",False
+frontiersci_research,FrontierSci-research,Science,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""FrontierSci-research""}",False
+genebench,GeneBench,Science,%,,https://openai.com/index/introducing-gpt-5-5/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Genomics benchmark."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""GeneBench""}",False
+gpqa_diamond,GPQA Diamond,Science,% correct,198.0,https://arxiv.org/abs/2311.12022,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""tools=none preferred (pure-reasoning eval). If only with-tool scores (python/web/RAG) are available, accept and mark cell matches_canonical=false."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""GPQA-Diamond (Rein et al. 2023)""}",True
+gpqa_main,GPQA Main (full set),Science,,448.0,https://arxiv.org/abs/2311.12022,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Full GPQA. Distinct from gpqa_diamond (198 hardest subset)."", ""range"": [0, 100], ""version"": ""GPQA full set (Rein et al. 2023, 448 questions)""}",True
+supergpqa,SuperGPQA,Science,%,,https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per DeepSeek V4-Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""SuperGPQA""}",True
+ainstein_bench,AInsteinBench,Science Discovery,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""AInsteinBench""}",False
+biobench,BIObench,Science Discovery,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""BIObench""}",False
+deepsearchqa_acc,DeepSearchQA (Accuracy),Search Agent,%,,https://huggingface.co/moonshotai/Kimi-K2.6,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Kimi K2.6 model card."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""DeepSearchQA (Accuracy)""}",True
+deepsearchqa_f1,DeepSearchQA (F1),Search Agent,%,,https://huggingface.co/moonshotai/Kimi-K2.6,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Kimi K2.6 model card."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""DeepSearchQA (F1)""}",False
+finsearchcomp,FinSearchComp,Search Agent,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""search"", ""version"": ""FinSearchComp""}",False
+finsearchcomp_global,FinSearchComp-Global,Search Agent,%,,https://huggingface.co/MiniMaxAI/MiniMax-M2,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per MiniMax M2 model card."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""FinSearchComp-Global""}",True
+finsearchcompt23,FinSearchComp T2&T3,Search Agent,%,,https://huggingface.co/moonshotai/Kimi-K2.5,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Kimi K2.5 model card."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""FinSearchComp T2&T3""}",False
+hle_text,HLE Text,Search Agent,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""search"", ""version"": ""HLE Text""}",True
+hle_verified,HLE Verified,Search Agent,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""search"", ""version"": ""HLE Verified""}",False
+seal_0,Seal-0,Search Agent,%,,https://huggingface.co/moonshotai/Kimi-K2.5,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Kimi K2.5 model card."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""Seal-0""}",False
+widesearch,WideSearch (item-F1),Search Agent,%,,https://huggingface.co/moonshotai/Kimi-K2.6,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Kimi K2.6 model card."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""WideSearch (item-F1)""}",True
+xbench_deepsearch,xbench-DeepSearch,Search Agent,%,,https://huggingface.co/MiniMaxAI/MiniMax-M2,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per MiniMax M2 model card."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""xbench-DeepSearch""}",True
+bfcl_v3_multiturn,BFCL v3 (Multi-Turn),Tool Use,%,,https://huggingface.co/deepseek-ai/DeepSeek-R1-0528,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per DeepSeek R1-0528 model card."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""BFCL v3 (Multi-Turn)""}",False
+bfcl_v4,BFCL v4,Tool Use,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""tool calls"", ""version"": ""BFCL v4""}",False
+complexfuncbench,ComplexFuncBench,Tool Use,%,,https://openai.com/index/gpt-4-1/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per OpenAI GPT-4.1 blog."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""ComplexFuncBench""}",True
+tau2_bench_avg,τ²-Bench (avg of retail/airline/telecom),Tool Use,%,,https://huggingface.co/MiniMaxAI/MiniMax-M2,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per MiniMax M2 model card."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""τ²-Bench (avg of retail/airline/telecom)""}",False
+tau3_bench,τ³-Bench,Tool Use,%,,https://z.ai/blog/glm-5.1,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per GLM-5.1 blog."", ""range"": [0, 100], ""tools"": ""agentic"", ""version"": ""τ³-Bench""}",True
+vitabench,VitaBench,Tool Use,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""tool calls"", ""version"": ""VitaBench""}",False
+bfcl,BFCL,Tool use,,,https://cohere.com/research/papers/command-a-technical-report.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Function calling benchmark. Distinct from bfcl_v3."", ""range"": [0, 100], ""version"": ""Berkeley Function Calling Leaderboard (Tau-bench predecessor)""}",True
+bfcl_v3,BFCL v3,Tool use,,,https://gorilla.cs.berkeley.edu/leaderboard.html,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Function-calling benchmark, FC format"", ""range"": [0, 100], ""version"": ""BFCL v3 (Berkeley Function Calling Leaderboard)""}",True
+tau1_bench_avg,"τ-bench (Yao 2024, averaged)",Tool use,,,https://cohere.com/research/papers/command-a-technical-report.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""τ-bench (Yao 2024) averaged. Distinct from per-domain cells (tau_bench_retail/airline/telecom)."", ""range"": [0, 100], ""version"": ""τ-bench averaged across retail+airline domains""}",False
+cgbench,CGBench,Video,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""CGBench""}",False
+contphy,ContPhy,Video,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""ContPhy""}",False
+crossvid,CrossVid,Video,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""CrossVid""}",False
+egoschema,EgoSchema (test),Video,,,https://egoschema.github.io/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Long-form egocentric video QA across multiple domains."", ""range"": [0, 100], ""version"": ""EgoSchema test split""}",False
+egotempo,EgoTempo,Video,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""EgoTempo""}",False
+livesports_3k,LiveSports-3K,Video,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""LiveSports-3K""}",False
+minerva,Minerva,Video,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""Minerva""}",False
+morse_500,Morse-500,Video,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""Morse-500""}",False
+odvbench,ODVBench,Video,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""ODVBench""}",False
+ovbench,OVBench,Video,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""OVBench""}",False
+ovobench,OVOBench,Video,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""OVOBench""}",False
+tempcompass,TempCompass,Video,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""TempCompass""}",False
+tomato,TOMATO,Video,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""TOMATO""}",False
+tvbench,TVBench,Video,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""TVBench""}",False
+videoeval_pro,VideoEval-Pro,Video,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""VideoEval-Pro""}",False
+videoholmes,VideoHolmes,Video,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""VideoHolmes""}",False
+videoreasonbench,VideoReasonBench,Video,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""VideoReasonBench""}",False
+videosimpleqa,VideoSimpleQA,Video,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""VideoSimpleQA""}",False
+vispeak,ViSpeak,Video,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""ViSpeak""}",False
+video_mmmu,Video-MMMU,Video/Multimodal,%,,https://deepmind.google/models/gemini/flash/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per DeepMind /models/gemini/flash/ Performance table. Knowledge acquisition from videos."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""Video-MMMU""}",True
+charxiv_descriptive,CharXiv Descriptive,Vision,%,,https://openai.com/index/gpt-4-1/,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per OpenAI GPT-4.1 blog."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""CharXiv Descriptive""}",True
+erqa,ERQA,Vision,%,400.0,https://github.com/embodiedreasoning/ERQA,"{""higher_is_better"": true, ""judge"": ""rule-based"", ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Official ERQA GitHub README says the full benchmark consists of 400 examples. Questions are multimodal interleaved images and text, phrased as multiple-choice questions, with answers provided as a single letter (A, B, C, D). The dataset covers embodied/spatial/trajectory/action/state-estimation reasoning for real-world robotics scenarios. HF mirrors GeorgeBredis/ERQA and FlagEval/ERQA both report 400 rows. Use exact letter accuracy; no LLM judge, tools, or agentic environment are part of the canonical benchmark."", ""range"": [0, 100], ""sampling"": ""single-pass"", ""tools"": ""none"", ""version"": ""ERQA full benchmark""}",True
+infovqa,InfoVQA (val),Vision,%,,https://huggingface.co/moonshotai/Kimi-K2.5,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Kimi K2.5 model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""InfoVQA (val)""}",False
+longvideobench,LongVideoBench,Vision,%,,https://huggingface.co/moonshotai/Kimi-K2.5,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Kimi K2.5 model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""LongVideoBench""}",False
+lvbench,LVBench,Vision,%,,https://huggingface.co/moonshotai/Kimi-K2.5,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Kimi K2.5 model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""LVBench""}",False
+mmvu,MMVU,Vision,%,,https://huggingface.co/moonshotai/Kimi-K2.5,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Kimi K2.5 model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""MMVU""}",False
+motionbench,MotionBench,Vision,%,,https://huggingface.co/moonshotai/Kimi-K2.5,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Kimi K2.5 model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""MotionBench""}",False
+omnidocbench,"OmniDocBench (normalized edit distance, lower is better)",Vision,edit distance (lower=better),,https://openai.com/index/introducing-gpt-5-4/,"{""higher_is_better"": false, ""metric_type"": ""edit_distance"", ""multimodal_input"": true, ""notes"": ""Doc OCR/parsing benchmark, scored as normalized edit distance (LOWER is better). Per OpenAI GPT-5.4 blog. | Standardized: edit distance, lower=better. If source reports 1-LED (higher-better), convert via score = 1 - x/100."", ""range"": [0, 1], ""tools"": ""none"", ""version"": ""OmniDocBench (normalized edit distance, lower is better)""}",True
+omnidocbench_1.5,OmniDocBench 1.5,Vision,edit distance (lower=better),,https://huggingface.co/moonshotai/Kimi-K2.5,"{""higher_is_better"": false, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Kimi K2.5 model card. | Standardized: edit distance, lower=better. If source reports 1-LED (higher-better), convert via score = 1 - x/100."", ""range"": [0, 1], ""tools"": ""none"", ""version"": ""OmniDocBench 1.5""}",True
+simplevqa,SimpleVQA,Vision,%,,https://huggingface.co/moonshotai/Kimi-K2.5,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Kimi K2.5 model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""SimpleVQA""}",False
+worldvqa,WorldVQA,Vision,%,,https://huggingface.co/moonshotai/Kimi-K2.5,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Kimi K2.5 model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""WorldVQA""}",False
+hle_vl,HLE-VL,Vision Agent,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""search"", ""version"": ""HLE-VL""}",False
+minedojo_verified,Minedojo Verified,Vision Agent,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""env"", ""version"": ""Minedojo Verified""}",False
+mm_browsecomp,MM-BrowseComp,Vision Agent,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""search"", ""version"": ""MM-BrowseComp""}",False
+countbench,CountBench,Vision Counting,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""CountBench""}",False
+fsc_147,FSC-147 (lower=better),Vision Counting,metric (lower=better),,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": false, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": null, ""tools"": ""none"", ""version"": ""FSC-147 (lower=better)""}",False
+point_bench,Point-Bench,Vision Counting,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""Point-Bench""}",False
+longdocurl,LongDocURL,Vision Long Context,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""LongDocURL""}",False
+mmlongbench,MMLongBench,Vision Long Context,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""MMLongBench""}",False
+mmlongbench_doc,MMLongBench-Doc,Vision Long Context,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""MMLongBench-Doc""}",False
+realworldqa,RealWorldQA,Vision Perception,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""RealWorldQA""}",False
+visfactor,VisFactor,Vision Perception,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""VisFactor""}",False
+vlms_are_biased,VLMsAreBiased,Vision Perception,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""VLMsAreBiased""}",False
+vlms_are_blind,VLMsAreBlind,Vision Perception,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""VLMsAreBlind""}",False
+arcagi1_image,ArcAGI1-Image,Vision Puzzles,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""ArcAGI1-Image""}",False
+arcagi2_image,ArcAGI2-Image,Vision Puzzles,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""ArcAGI2-Image""}",False
+visulogic,VisuLogic,Vision Puzzles,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""VisuLogic""}",False
+vpct,VPCT,Vision Puzzles,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""VPCT""}",False
+zerobench_main,ZeroBench (main),Vision Puzzles,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""ZeroBench (main)""}",False
+zerobench_sub,ZeroBench (sub),Vision Puzzles,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""ZeroBench (sub)""}",False
+logicvista,LogicVista,Vision Reasoning,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""LogicVista""}",False
+emma,EMMA,Vision STEM,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""EMMA""}",False
+hipho,HiPhO,Vision STEM,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""HiPhO""}",False
+phyx_openended,PhyX (open-ended),Vision STEM,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""PhyX (open-ended)""}",False
+sfe,SFE,Vision STEM,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""SFE""}",False
+xlrs_macro,XLRS-Bench (macro),Vision STEM,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""XLRS-Bench (macro)""}",False
+all_angles,All-Angles,Vision Spatial,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""All-Angles""}",False
+blink,BLINK,Vision Spatial,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""BLINK""}",False
+da_2k,DA-2K,Vision Spatial,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""DA-2K""}",False
+mmsibench_circular,MMSIBench (circular),Vision Spatial,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""MMSIBench (circular)""}",False
+refspatialbench,RefSpatialBench,Vision Spatial,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""RefSpatialBench""}",False
+treebench,TreeBench,Vision Spatial,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""TreeBench""}",False
+hallusionbench,HallusionBench,Vision VQA,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""HallusionBench""}",False
+mme_cc,MME-CC,Vision VQA,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""MME-CC""}",False
+mmstar,MMStar,Vision VQA,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""MMStar""}",False
+mtvqa,MTVQA,Vision VQA,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""MTVQA""}",False
+muirbench,MUIRBench,Vision VQA,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""MUIRBench""}",False
+viverbench,ViVerBench,Vision VQA,%,,https://lf3-static.bytednsdoc.com/obj/eden-cn/lapzild-tss/ljhwZthlaukjlkulzlp/seed2/0214/Seed2.0%20Model%20Card.pdf,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": true, ""notes"": ""Per Doubao Seed 2.0 Pro model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""ViVerBench""}",False
+longform_writing,Longform Writing,Writing,%,,https://huggingface.co/moonshotai/Kimi-K2-Thinking,"{""higher_is_better"": true, ""metric_type"": ""pct"", ""multimodal_input"": false, ""notes"": ""Per Kimi K2-Thinking model card."", ""range"": [0, 100], ""tools"": ""none"", ""version"": ""Longform Writing""}",False