#5151st of 53 in Gateways and observability

simple-evals

Reference implementations of zero-shot LLM benchmarks such as MMLU, GPQA and SimpleQA

Stars
4.7k
License
MIT
Last commit
Apr 2026
Language
Python
Stars, last 29 weeks+294
22 Apr 2026: 4,408 stars29 Apr 2026: 4,424 stars6 May 2026: 4,435 stars13 May 2026: 4,447 stars20 May 2026: 4,454 stars27 May 2026: 4,471 stars3 Jun 2026: 4,481 stars10 Jun 2026: 4,492 stars17 Jun 2026: 4,499 stars24 Jun 2026: 4,515 stars1 Jul 2026: 4,531 stars8 Jul 2026: 4,540 stars15 Jul 2026: 4,548 stars22 Jul 2026: 4,557 stars29 Jul 2026: 4,569 stars5 Aug 2026: 4,576 stars12 Aug 2026: 4,579 stars19 Aug 2026: 4,591 stars26 Aug 2026: 4,597 stars2 Sept 2026: 4,608 stars9 Sept 2026: 4,613 stars16 Sept 2026: 4,620 stars23 Sept 2026: 4,627 stars30 Sept 2026: 4,638 stars7 Oct 2026: 4,642 stars14 Oct 2026: 4,656 stars21 Oct 2026: 4,665 stars28 Oct 2026: 4,679 stars4 Nov 2026: 4,694 stars11 Nov 2026: 4,702 stars

4,408 on 22 Apr 20264,702 on 11 Nov 2026

From GitHub's daily star counts.

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Overview

A small Python library from OpenAI that runs language-model evals (MMLU, MATH, GPQA, DROP, MGSM, HumanEval, SimpleQA, BrowseComp, HealthBench) with zero-shot chain-of-thought prompts. Samplers exist for the OpenAI and Anthropic APIs, driven by a CLI. Since July 2025 it is no longer updated for new models and only keeps the HealthBench, BrowseComp and SimpleQA reference implementations.

Who it is for: Engineers reproducing OpenAI benchmark numbers or reading reference eval code

Strengths

  • Covers nine benchmarks behind one CLI: --model and --examples flags
  • Zero-shot chain-of-thought prompts with simple instructions, documented in the README
  • Official reference code for SimpleQA, BrowseComp and HealthBench
  • Published results table gives baseline numbers for many OpenAI and third-party models

Weaknesses

  • Deprecated: no updates for new models or benchmark results after July 2025
  • Maintainers do not monitor issues or PRs, and no new evals are accepted
  • No unified setup; each eval and sampler needs its own pip install
  • Samplers only for OpenAI and Claude APIs; no local model backend

What it needs

  • no GPU
  • Needs openai, anthropic, human-eval
  • Models: OpenAI API, Anthropic Claude API

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