Artificial Analysis

Artificial Analysis is an independent benchmarking platform that evaluates and compares AI models and API hosting providers across key metrics including intelligence, output speed, latency, price, and context window size. It provides standardized, reproducible evaluations that help developers and organizations choose between models and providers based on real-world performance data rather than vendor claims.

The platform's Intelligence Index (v4.0) aggregates scores across multiple evaluation categories, each weighted equally, covering reasoning, knowledge, coding, and specialized tasks. It includes benchmarks like GPQA Diamond, Humanity's Last Exam, and its own proprietary evaluations such as AA-Omniscience (a knowledge and hallucination benchmark that penalizes incorrect guesses) and AA-LCR (long context retrieval). This composite approach provides a more balanced view of model capability than any single benchmark.

Beyond model intelligence, Artificial Analysis measures the end-to-end inference performance that customers actually experience across different API providers, including time to first token, tokens per second, and total response time under varying concurrency loads. It also benchmarks AI accelerator hardware, comparing chips like NVIDIA H100, AMD MI300X, and others for inference throughput. The platform has become a widely referenced source in AI industry reporting and model comparison discussions.