--- title: "lmms-eval vs promptfoo" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/evolvinglmms-lab-lmms-eval-vs-promptfoo-promptfoo" tools: ["evolvinglmms-lab-lmms-eval", "promptfoo-promptfoo"] --- # lmms-eval vs promptfoo Neutral, constraint-first comparison with live GitHub stats. | | [lmms-eval](/tools/evolvinglmms-lab-lmms-eval.md) | [promptfoo](/tools/promptfoo-promptfoo.md) | | --- | --- | --- | | Tagline | Unified Evaluation Toolkit for Multimodal Large Language Models | CLI and library for evaluating and red-teaming LLM apps | | Stars | 4,292 | 23,045 | | Forks | 613 | 2,056 | | Open issues | 43 | 404 | | Language | Python | TypeScript | | Adopt for | lmms-eval is a unified evaluation toolkit designed to assess multimodal large language models across various tasks including text, image, video, and audio with a focus on reproducibility and efficiency. | Promptfoo is a CLI and library for evaluating Language Model (LM) applications, including testing prompts and models, red teaming LM apps, and integrating with CI/CD pipelines. It's designed to help ensure the security,靠 | | Persona | - | - | | Runtime | - | - | | License | Other | MIT | | Categories | Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [lmms-eval](/tools/evolvinglmms-lab-lmms-eval.md) | [promptfoo](/tools/promptfoo-promptfoo.md) | | --- | --- | --- | | Days since push | 1d | 0d | | Open issues (now) | 43 | 404 | | Security scan | Not scanned | No lockfile | | Full report | [trust report](/tools/evolvinglmms-lab-lmms-eval/trust.md) | [trust report](/tools/promptfoo-promptfoo/trust.md) | **Typed relationship:** lmms-eval _(alternative)_ promptfoo Both tools are designed to evaluate LLMs by providing ways to test and red-team LLM applications, but they use different methodologies for evaluation. ## Decision facts: lmms-eval - **Adopt for:** lmms-eval is a unified evaluation toolkit designed to assess multimodal large language models across various tasks including text, image, video, and audio with a focus on reproducibility and efficiency. ## Decision facts: promptfoo - **Adopt for:** Promptfoo is a CLI and library for evaluating Language Model (LM) applications, including testing prompts and models, red teaming LM apps, and integrating with CI/CD pipelines. It's designed to help ensure the security,靠 ## Choose when ### Choose lmms-eval if… - lmms-eval is primarily Python; promptfoo is TypeScript. - License: lmms-eval is Other, promptfoo is MIT. - Both tools are designed to evaluate LLMs by providing ways to test and red-team LLM applications, but they use different methodologies for evaluation. - Tags unique to lmms-eval: benchmark, large-language-models, multimodal-evaluation. - Use lmms-eval when you need a single, comprehensive solution for evaluating the performance of large language models (LLMs) in multiple modalities. ### Choose promptfoo if… - promptfoo is primarily TypeScript; lmms-eval is Python. - License: promptfoo is MIT, lmms-eval is Other. - Both tools are designed to evaluate LLMs by providing ways to test and red-team LLM applications, but they use different methodologies for evaluation. - Tags unique to promptfoo: ci-cd, evaluation, prompt-testing, prompt-engineering. - promptfoo ships Docker support for self-hosted deployment. - When you need to evaluate the performance of different LLMs such as OpenAI, Anthropic, Azure, Bedrock, Ollama, etc., within a single interface. ## When NOT to use lmms-eval - Avoid using lmms-eval for single-modality evaluations where a narrower or more specialized toolkit could be more appropriate. - If reproducibility is not a primary concern in your model development workflow, then lmms-eval’s strict adherence to providing deterministic results through its unified pipeline may offer no clear优势。 - 如果你的评估流程不需要高性能和可信赖的结果，或者你的团队不需要支持多项任务和多个模型的统一工具，则不建议使用lmms-eval。它的高效性和信任度可能是其核心特点，但如果这些对于你的用例不是关键需求，那么它可能并不是最佳选择。 ## When NOT to use promptfoo - When your environment does not support Node.js, as this is a requirement for Promptfoo's functionalities. - If you are looking for a tool that only focuses on model training or fine-tuning without the emphasis on evaluation and red-teaming aspects of language models. ## Common questions ### What is the difference between lmms-eval and promptfoo? lmms-eval: Unified Evaluation Toolkit for Multimodal Large Language Models. promptfoo: CLI and library for evaluating and red-teaming LLM apps. See the comparison table for live GitHub stats and shared categories. ### When should I choose lmms-eval over promptfoo? Choose lmms-eval over promptfoo when lmms-eval is primarily Python; promptfoo is TypeScript; License: lmms-eval is Other, promptfoo is MIT; Both tools are designed to evaluate LLMs by providing ways to test and red-team LLM applications, but they use different methodologies for evaluation; Tags unique to lmms-eval: benchmark, large-language-models, multimodal-evaluation; Use lmms-eval when you need a single, comprehensive solution for evaluating the performance of large language models (LLMs) in multiple modalities. ### When should I choose promptfoo over lmms-eval? Choose promptfoo over lmms-eval when promptfoo is primarily TypeScript; lmms-eval is Python; License: promptfoo is MIT, lmms-eval is Other; Both tools are designed to evaluate LLMs by providing ways to test and red-team LLM applications, but they use different methodologies for evaluation; Tags unique to promptfoo: ci-cd, evaluation, prompt-testing, prompt-engineering; promptfoo ships Docker support for self-hosted deployment; When you need to evaluate the performance of different LLMs such as OpenAI, Anthropic, Azure, Bedrock, Ollama, etc., within a single interface. ### When should I avoid lmms-eval? Avoid using lmms-eval for single-modality evaluations where a narrower or more specialized toolkit could be more appropriate. If reproducibility is not a primary concern in your model development workflow, then lmms-eval’s strict adherence to providing deterministic results through its unified pipeline may offer no clear优势。 如果你的评估流程不需要高性能和可信赖的结果，或者你的团队不需要支持多项任务和多个模型的统一工具，则不建议使用lmms-eval。它的高效性和信任度可能是其核心特点，但如果这些对于你的用例不是关键需求，那么它可能并不是最佳选择。 ### When should I avoid promptfoo? When your environment does not support Node.js, as this is a requirement for Promptfoo's functionalities. If you are looking for a tool that only focuses on model training or fine-tuning without the emphasis on evaluation and red-teaming aspects of language models. ### Is lmms-eval or promptfoo more popular on GitHub? promptfoo has more GitHub stars (23,045 vs 4,292). Stars measure visibility, not whether either tool fits your constraints. ### Are lmms-eval and promptfoo open source? Yes - both are open-source projects on GitHub (lmms-eval: Other, promptfoo: MIT). ### Where can I find alternatives to lmms-eval or promptfoo? GraphCanon lists graph-backed alternatives at /tools/evolvinglmms-lab-lmms-eval/alternatives and /tools/promptfoo-promptfoo/alternatives (/tools/evolvinglmms-lab-lmms-eval/alternatives.md, /tools/promptfoo-promptfoo/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 /compare/evolvinglmms-lab-lmms-eval-vs-promptfoo-promptfoo.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, lmms-eval or promptfoo? lmms-eval: Very active. promptfoo: Very active. 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 lmms-eval and promptfoo? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: lmms-eval: /tools/evolvinglmms-lab-lmms-eval/trust; promptfoo: /tools/promptfoo-promptfoo/trust. --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=evolvinglmms-lab-lmms-eval`](/api/graphcanon/graph?tool=evolvinglmms-lab-lmms-eval) - 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/_