metadata
license: cc-by-4.0
tags:
- llm
- benchmarks
- ai-evaluation
- model-comparison
- features
- rate-limits
size_categories:
- n<1K
LLM Benchmark & Feature Matrix 2026
Which LLM is best at what? This dataset maps capabilities, performance, and limits of 22 major models.
Unlike pricing datasets, this focuses on what models can do — not just what they cost.
Files
| File | Description |
|---|---|
llm-benchmarks-2026.csv |
MMLU, HumanEval, MATH, Arena ELO, coding/reasoning/multilingual rankings, tier (S+ to B) |
llm-features-2026.csv |
15 binary capabilities: vision, function calling, JSON mode, fine-tuning, tool use, web search, embeddings... |
llm-rate-limits-2026.csv |
Free tier availability, RPM/TPM limits, batch discounts, cached input discounts |
Models Covered
22 models from OpenAI, Anthropic, Google, Meta, Mistral, DeepSeek, xAI, Cohere
Use Cases
- Model selection — Find models that support your required features (e.g., vision + function calling + fine-tuning)
- Performance comparison — Which model scores highest on coding vs reasoning vs multilingual?
- Rate limit planning — Can you stay within free tier? What are the paid RPM limits?
- Tier analysis — S+ tier models vs A tier — is the premium worth it?
Key Insights
- Only Google Gemini supports all 15 features (vision, search, embeddings, fine-tuning, code execution)
- DeepSeek offers 90% cached input discount — massive savings for repetitive workloads
- Groq has highest free tier RPM (30) with lowest latency
- S+ tier models (o1, Claude Opus 4, Gemini 2.5 Pro, DeepSeek R1) all score >89 MMLU
Related
- LLM Rankings — Live leaderboard
- AI Tools Pricing Dataset — 104 AI tools
- Kaggle: Full Pricing Data
- GitHub Open Data
License
CC BY 4.0 — ComparEdge