--- title: "mteb vs lighteval" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/embeddings-benchmark-mteb-vs-huggingface-lighteval" tools: ["embeddings-benchmark-mteb", "huggingface-lighteval"] --- # mteb vs lighteval *GraphCanon updated Jul 12, 2026* ## Verdict Pick mteb when license: mteb is Apache-2.0, lighteval is MIT; pick lighteval when license: lighteval is MIT, mteb is Apache-2.0. [mteb](https://docs.mteb.org) reports 3.3k GitHub stars, 638 forks, and 295 open issues, last pushed Jul 9, 2026. [lighteval](https://huggingface.co/docs/lighteval/en/index) has 2.5k stars, 506 forks, and 347 open issues, last pushed Jun 29, 2026. Figures are from public GitHub metadata via [mteb's repository](https://github.com/embeddings-benchmark/mteb) and [lighteval's repository](https://github.com/huggingface/lighteval). | | [mteb](/tools/embeddings-benchmark-mteb.md) | [lighteval](/tools/huggingface-lighteval.md) | | --- | --- | --- | | Tagline | State-of-the-art evaluation of embeddings across languages and modalities | All-in-one toolkit for evaluating LLMs across multiple backends | | Stars | 3,349 | 2,472 | | Forks | 638 | 506 | | Open issues | 295 | 347 | | Language | Python | Python | | Adopt for | - | Lighteval is designed for evaluating language models across multiple backends. It integrates well with Hugging Face and provides a wide range of extras, making it particularly handy in non-Windows environments. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [mteb](/tools/embeddings-benchmark-mteb.md) | [lighteval](/tools/huggingface-lighteval.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 1d | 11d | | Open issues (now) | 295 | 347 | | Full report | [trust report](/tools/embeddings-benchmark-mteb/trust.md) | [trust report](/tools/huggingface-lighteval/trust.md) | ## Decision facts: lighteval - **Adopt for:** Lighteval is designed for evaluating language models across multiple backends. It integrates well with Hugging Face and provides a wide range of extras, making it particularly handy in non-Windows environments. ## Choose when ### Choose mteb if… - License: mteb is Apache-2.0, lighteval is MIT. - Tags unique to mteb: benchmark, embeddings, information-retrieval, multilingual-nlp. - mteb ships Docker support for self-hosted deployment. ### Choose lighteval if… - License: lighteval is MIT, mteb is Apache-2.0. - Tags unique to lighteval: evaluation framework, evaluation-metrics, huggingface, python. - When you need to evaluate the performance of various LLMs on different backend infrastructures, especially if you are working within Mac/Linux environments. ## When NOT to use mteb - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. ## When NOT to use lighteval - Avoid Lighteval for evaluations on Windows systems as it is currently untested and not supported there. - Should you require a solution that does not integrate with or depend on the Hugging Face ecosystem, Lighteval might not fulfill your needs. ## Common questions ### What is the difference between mteb and lighteval? mteb: State-of-the-art evaluation of embeddings across languages and modalities. lighteval: All-in-one toolkit for evaluating LLMs across multiple backends. See the comparison table for live GitHub stats and shared categories. ### When should I choose mteb over lighteval? Choose mteb over lighteval when License: mteb is Apache-2.0, lighteval is MIT; Tags unique to mteb: benchmark, embeddings, information-retrieval, multilingual-nlp; mteb ships Docker support for self-hosted deployment. ### When should I choose lighteval over mteb? Choose lighteval over mteb when License: lighteval is MIT, mteb is Apache-2.0; Tags unique to lighteval: evaluation framework, evaluation-metrics, huggingface, python; When you need to evaluate the performance of various LLMs on different backend infrastructures, especially if you are working within Mac/Linux environments. ### When should I avoid mteb? Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. ### When should I avoid lighteval? Avoid Lighteval for evaluations on Windows systems as it is currently untested and not supported there. Should you require a solution that does not integrate with or depend on the Hugging Face ecosystem, Lighteval might not fulfill your needs. ### Is mteb or lighteval more popular on GitHub? mteb has more GitHub stars (3,349 vs 2,472). Stars measure visibility, not whether either tool fits your constraints. ### Are mteb and lighteval open source? Yes - both are open-source projects on GitHub (mteb: Apache-2.0, lighteval: MIT). ### Where can I find alternatives to mteb or lighteval? GraphCanon lists graph-backed alternatives at [mteb alternatives](/tools/embeddings-benchmark-mteb/alternatives) and [lighteval alternatives](/tools/huggingface-lighteval/alternatives) ([mteb markdown twin](/tools/embeddings-benchmark-mteb/alternatives.md), [lighteval markdown twin](/tools/huggingface-lighteval/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/embeddings-benchmark-mteb-vs-huggingface-lighteval.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, mteb or lighteval? mteb: Very active. lighteval: 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 mteb and lighteval? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [mteb trust report](/tools/embeddings-benchmark-mteb/trust); [lighteval trust report](/tools/huggingface-lighteval/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=embeddings-benchmark-mteb`](/api/graphcanon/graph?tool=embeddings-benchmark-mteb) - 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/_