Add/update skill card: gpt-5.6-sol
Browse files- gpt-5.6-sol.json +36 -0
- index.json +35 -29
gpt-5.6-sol.json
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{
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"model": "gpt-5.6-sol",
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"provider": "openai",
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"capabilities": [
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"coding",
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"creative_synthesis",
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"instruction_following",
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"math_reasoning",
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"planning_agentic",
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"world_knowledge"
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],
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"skill_vector": [
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0.9,
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0.91,
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0.86,
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0.94,
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0.92,
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0.94
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],
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"source": "benchmark",
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"confidence": [
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"high",
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"low",
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"medium",
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"medium",
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"high",
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"medium"
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],
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"imputed_capabilities": [
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"creative_synthesis"
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],
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"support": null,
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"subset_hash": null,
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"date": "2026-07-12",
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"notes": "Benchmark-derived skill vector for GPT-5.6 Sol (flagship tier, released 2026-07-09). OpenAI's launch suite is deliberately agentic and omits AIME/GPQA/MMLU/IFEval, so only coding and planning_agentic have direct public benchmarks (confidence high); math/world/instruction are anchored to the composite intelligence index (confidence medium); creative_synthesis is imputed (confidence low). Sourcing per dimension: coding=Terminal-Bench 2.1 88.8% (SOTA) + Artificial Analysis Coding Agent Index 80/100 (SOTA); planning_agentic=Agents' Last Exam 53.6 (SOTA, +13 over Fable 5) + OSWorld 2.0 62.6% (SOTA); math_reasoning + world_knowledge=Artificial Analysis Intelligence Index v4.1 Sol=59 (near-top), no standalone AIME/GPQA published; instruction_following=no public IFEval, estimated from the composite index; creative_synthesis=imputed as the mean of the known coordinates. Sources: openai.com/index/gpt-5-6, artificialanalysis.ai/articles/gpt-5-6-has-landed, vellum.ai/blog/gpt-5-6-benchmarks-explained. A `measured` extraction on the frozen probe set overrides this. See README.md."
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}
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index.json
CHANGED
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"planning_agentic",
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"world_knowledge"
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],
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"date": "2026-
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"models": [
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{
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"model": "claude-opus-4-8",
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"provider": "anthropic",
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"source": "benchmark"
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},
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{
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"model": "
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"provider": "
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"file": "
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"source": "benchmark"
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},
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"model": "
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"provider": "
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"file": "
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"source": "benchmark"
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"model": "
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"provider": "
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"file": "
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"source": "benchmark"
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},
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"model": "
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"provider": "
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"file": "
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"source": "benchmark"
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},
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{
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"model": "
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"provider": "openai",
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"file": "
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"source": "benchmark"
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},
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"model": "
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"provider": "openai",
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"file": "
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"source": "benchmark"
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"source": "benchmark"
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"source": "benchmark"
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"model": "
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"source": "benchmark"
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"model": "
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"provider": "
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"file": "
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"source": "benchmark"
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}
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]
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"planning_agentic",
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"world_knowledge"
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],
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"date": "2026-07-12",
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"models": [
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{
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"model": "claude-haiku-4-5",
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"provider": "anthropic",
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"file": "claude-haiku-4-5.json",
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"source": "benchmark"
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},
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{
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"model": "claude-opus-4-8",
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"provider": "anthropic",
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"source": "benchmark"
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},
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{
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"model": "gemini-2.5-pro",
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"provider": "google",
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"file": "gemini-2.5-pro.json",
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"source": "benchmark"
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},
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{
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"model": "gemini-3.1-flash-lite",
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"provider": "google",
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"file": "gemini-3.1-flash-lite.json",
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"source": "benchmark"
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},
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{
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"model": "gemini-3.1-pro",
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"provider": "google",
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"file": "gemini-3.1-pro.json",
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"source": "benchmark"
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},
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{
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"model": "gemini-3.5-flash",
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"provider": "google",
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"file": "gemini-3.5-flash.json",
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"source": "benchmark"
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},
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{
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"model": "gpt-5.4",
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"provider": "openai",
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"file": "gpt-5.4.json",
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"source": "benchmark"
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},
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{
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"model": "gpt-5.4-mini",
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"provider": "openai",
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"file": "gpt-5.4-mini.json",
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"source": "benchmark"
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},
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{
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"model": "gpt-5.5",
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"provider": "openai",
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"file": "gpt-5.5.json",
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"source": "benchmark"
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},
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{
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"model": "gpt-5.6-sol",
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"provider": "openai",
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"file": "gpt-5.6-sol.json",
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"source": "benchmark"
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},
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{
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"model": "o3",
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"provider": "openai",
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"file": "o3.json",
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"source": "benchmark"
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},
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{
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"model": "o3-mini",
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"provider": "openai",
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"file": "o3-mini.json",
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"source": "benchmark"
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}
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]
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