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Mini toolsAI benchmarks
Browse benchmarks tracking how AI models perform on reasoning, coding, multimodal and knowledge tasks. Each benchmark has its own leaderboard with the latest results from frontier models.
Cross-benchmark model leaderboard
Compare how every tracked model ranks across the headline benchmarks in one matrix.
Aider Polyglot
225 hard Exercism programming exercises across 6 languages (C++, Go, Java, JavaScript, Python, Rust). Measures whole-file edit accuracy under realistic agentic-coding harness.
CodeForces ELO
Live competitive-programming ELO inferred from a model's performance on recent Codeforces rounds. Reported as a Codeforces rating.
HumanEval Saturated
OpenAI's 164 hand-written Python programming problems with unit tests. The original code-LLM benchmark; now saturated and broadly considered contaminated in modern training corpo…
HumanEval+ Saturated
HumanEval with substantially expanded test cases (~80x more) to catch wrong-but-passing solutions.
LiveCodeBench
Continuously refreshed competitive-programming problems sourced from LeetCode, AtCoder, and Codeforces after the model's knowledge cutoff. Designed to stay contamination-free.
MBPP Saturated
974 short Python problems with test cases. One of the original code-LLM benchmarks; saturated by frontier models.
SWE-bench Multimodal
Variant of SWE-bench where issues include screenshots, diagrams and other visual context. Tests multimodal software-engineering ability.
SWE-bench Verified
500 manually validated GitHub issues from popular Python repos. Models must produce a patch that passes the hidden test suite. The current standard for "real software engineering…
