Artificial Analysis
Canonical version: Artificial Analysis.
Artificial Analysis is an independent benchmarking and comparison platform for AI models and inference providers. It tracks frontier models across providers like OpenAI, Anthropic, Google (Gemini), Meta, DeepSeek, Mistral, and xAI; scoring each on quality, speed (tokens/sec), latency (time-to-first-token), context window, and price (input/output tokens).
What makes it useful:
- Side-by-side model comparisons on a single intelligence index aggregating multiple benchmarks (MMLU-Pro, GPQA, MATH, HumanEval, etc.).
- Provider-level comparisons for the same model; e.g., Llama 3.1 405B served by Together vs Fireworks vs Groq, with measured throughput and price.
- Coverage beyond text: image generation, image editing, video generation, speech-to-text, and text-to-speech leaderboards.
- Regular API speed tests, so the data reflects real inference performance rather than vendor claims.
When to use it:
- Choosing a model for a specific job; balance intelligence vs latency vs cost.
- Evaluating which inference provider to use for an open-weights model.
- Tracking how the frontier evolves over time without manually scraping each lab.
References
- Official website: https://artificialanalysis.ai/
- Methodology: https://artificialanalysis.ai/methodology
- Leaderboards: https://artificialanalysis.ai/leaderboards/models
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