--- title: "awesome-evals vs simple-evals" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/benchflow-ai-awesome-evals-vs-openai-simple-evals" tools: ["benchflow-ai-awesome-evals", "openai-simple-evals"] --- # awesome-evals vs simple-evals *GraphCanon updated Aug 7, 2026* ## Verdict Pick awesome-evals if curated resources for AI agent evaluation with BenchFlow backing its maintenance; pick simple-evals if simple-evals provides lightweight tools for evaluating language models using reference implementations from HealthBench, BrowseComp, SimpleQA. Last updates July 2025. [awesome-evals](https://github.com/benchflow-ai/awesome-evals) reports 761 GitHub stars, 71 forks, and 21 open issues, last pushed Jul 1, 2026. [simple-evals](https://github.com/openai/simple-evals) has 4.6k stars, 501 forks, and 56 open issues, last pushed Apr 22, 2026. Figures are from public GitHub metadata via [awesome-evals's repository](https://github.com/benchflow-ai/awesome-evals) and [simple-evals's repository](https://github.com/openai/simple-evals). | | [awesome-evals](/tools/benchflow-ai-awesome-evals.md) | [simple-evals](/tools/openai-simple-evals.md) | | --- | --- | --- | | Tagline | A curated library of resources for building and evaluating AI agents | A lightweight library for evaluating language models. | | Stars | 761 | 4,595 | | Forks | 71 | 501 | | Open issues | 21 | 56 | | Language | - | Python | | Adopt for | Curated resources for AI agent evaluation with BenchFlow backing its maintenance | simple-evals provides lightweight tools for evaluating language models using reference implementations from HealthBench, BrowseComp, SimpleQA. Last updates July 2025. | | Persona | - | - | | Runtime | - | - | | License | Other | MIT licensed Python library for transparent language model evaluations with specific benchmark support until July 2025. | | Categories | AI Agents, Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [awesome-evals](/tools/benchflow-ai-awesome-evals.md) | [simple-evals](/tools/openai-simple-evals.md) | | --- | --- | --- | | Maintenance | Active (82%) | Slowing (36%) | | Days since push | 26d | 106d | | Open issues (now) | 21 | 56 | | Full report | [trust report](/tools/benchflow-ai-awesome-evals/trust.md) | [trust report](/tools/openai-simple-evals/trust.md) | ## Decision facts: awesome-evals - **Adopt for:** Curated resources for AI agent evaluation with BenchFlow backing its maintenance ## Decision facts: simple-evals - **Adopt for:** simple-evals provides lightweight tools for evaluating language models using reference implementations from HealthBench, BrowseComp, SimpleQA. Last updates July 2025. - **License detail:** MIT licensed Python library for transparent language model evaluations with specific benchmark support until July 2025. ## Choose when ### Choose awesome-evals if… - License: awesome-evals is Other, simple-evals is MIT. - Tags unique to awesome-evals: agent-evaluation, ai-agents, awesome-list, benchmarks. - Also covers AI Agents. - Need diverse resources encompassing papers, blogs, talks, tools, and benchmarks specifically curated for AI agent evaluation ### Choose simple-evals if… - License: simple-evals is MIT, awesome-evals is Other. - Tags unique to simple-evals: benchmark, depreciation notice, evaluation, language-models. - When you need a stable baseline to evaluate model performance with specific benchmarks like MMLU, HumanEval, and DROP that won't change after July 2025 ## When NOT to use awesome-evals - Require real-time interactive support or direct tool integrations not covered by a static resource list - Seeking proprietary tools from specific vendors rather than open resources and community content ## When NOT to use simple-evals - For evaluating models released or significantly updated after July 2025, as this tool does not include future benchmarks - When you need a tool that will adapt and expand its benchmark set with emerging model releases and evaluation tasks beyond 2025 ## Common questions ### What is the difference between awesome-evals and simple-evals? awesome-evals: A curated library of resources for building and evaluating AI agents. simple-evals: A lightweight library for evaluating language models.. See the comparison table for live GitHub stats and shared categories. ### When should I choose awesome-evals over simple-evals? Choose awesome-evals over simple-evals when License: awesome-evals is Other, simple-evals is MIT; Tags unique to awesome-evals: agent-evaluation, ai-agents, awesome-list, benchmarks; Also covers AI Agents; Need diverse resources encompassing papers, blogs, talks, tools, and benchmarks specifically curated for AI agent evaluation. ### When should I choose simple-evals over awesome-evals? Choose simple-evals over awesome-evals when License: simple-evals is MIT, awesome-evals is Other; Tags unique to simple-evals: benchmark, depreciation notice, evaluation, language-models; When you need a stable baseline to evaluate model performance with specific benchmarks like MMLU, HumanEval, and DROP that won't change after July 2025. ### When should I avoid awesome-evals? Require real-time interactive support or direct tool integrations not covered by a static resource list Seeking proprietary tools from specific vendors rather than open resources and community content ### When should I avoid simple-evals? For evaluating models released or significantly updated after July 2025, as this tool does not include future benchmarks When you need a tool that will adapt and expand its benchmark set with emerging model releases and evaluation tasks beyond 2025 ### Is awesome-evals or simple-evals more popular on GitHub? simple-evals has more GitHub stars (4,595 vs 761). Stars measure visibility, not whether either tool fits your constraints. ### Are awesome-evals and simple-evals open source? Yes - both are open-source projects on GitHub (awesome-evals: Other, simple-evals: MIT). ### Where can I find alternatives to awesome-evals or simple-evals? GraphCanon lists graph-backed alternatives at [awesome-evals alternatives](/tools/benchflow-ai-awesome-evals/alternatives) and [simple-evals alternatives](/tools/openai-simple-evals/alternatives) ([awesome-evals markdown twin](/tools/benchflow-ai-awesome-evals/alternatives.md), [simple-evals markdown twin](/tools/openai-simple-evals/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/benchflow-ai-awesome-evals-vs-openai-simple-evals.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, awesome-evals or simple-evals? awesome-evals: Active. simple-evals: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for awesome-evals and simple-evals? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [awesome-evals trust report](/tools/benchflow-ai-awesome-evals/trust); [simple-evals trust report](/tools/openai-simple-evals/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=benchflow-ai-awesome-evals`](/api/graphcanon/graph?tool=benchflow-ai-awesome-evals) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_