--- title: "athina-evals vs mteb" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/athina-ai-athina-evals-vs-embeddings-benchmark-mteb" tools: ["athina-ai-athina-evals", "embeddings-benchmark-mteb"] --- # athina-evals vs mteb *GraphCanon updated Aug 22, 2026* ## Verdict Pick athina-evals if athina-evals is a Python SDK developed for facilitating the evaluation of outputs from large language models through predefined metrics and frameworks; pick mteb if mTEB is an evaluator for embedding models across languages and modalities under the Apache-2.0 license. [athina-evals](https://docs.athina.ai) reports 301 GitHub stars, 22 forks, and 3 open issues, last pushed Jun 6, 2025. [mteb](https://docs.mteb.org) has 3.4k stars, 670 forks, and 340 open issues, last pushed Aug 21, 2026. Figures are from public GitHub metadata via [athina-evals's repository](https://github.com/athina-ai/athina-evals) and [mteb's repository](https://github.com/embeddings-benchmark/mteb). | | [athina-evals](/tools/athina-ai-athina-evals.md) | [mteb](/tools/embeddings-benchmark-mteb.md) | | --- | --- | --- | | Tagline | Python SDK for evaluating LLM generated responses | State-of-the-art evaluation of embeddings across languages and modalities | | Stars | 301 | 3,400 | | Forks | 22 | 670 | | Open issues | 3 | 340 | | Language | Python | Python | | Adopt for | athina-evals is a Python SDK developed for facilitating the evaluation of outputs from large language models through predefined metrics and frameworks. | MTEB is an evaluator for embedding models across languages and modalities under the Apache-2.0 license. | | Persona | - | - | | Runtime | - | - | | License | - | Apache-2.0 | | Categories | Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [athina-evals](/tools/athina-ai-athina-evals.md) | [mteb](/tools/embeddings-benchmark-mteb.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 417d | 0d | | Open issues (now) | 3 | 340 | | Stars delta | Unknown | +36 (30d) | | Open issues delta | Unknown | +31 (30d) | | Full report | [trust report](/tools/athina-ai-athina-evals/trust.md) | [trust report](/tools/embeddings-benchmark-mteb/trust.md) | ## Decision facts: athina-evals - **Adopt for:** athina-evals is a Python SDK developed for facilitating the evaluation of outputs from large language models through predefined metrics and frameworks. ## Decision facts: mteb - **Adopt for:** MTEB is an evaluator for embedding models across languages and modalities under the Apache-2.0 license. ## Choose when ### Choose athina-evals if… - Tags unique to athina-evals: evaluation, evaluation-framework, evaluation-metrics, llm-eval. - When comprehensive evaluation of LLM responses is required, leveraging athina's specific tools and metrics - Leaner open-issue backlog (3). ### Choose mteb if… - Tags unique to mteb: benchmark, bitext-mining, clustering, embeddings. - mteb ships Docker support for self-hosted deployment. - You require benchmarking tools specifically designed for state-of-the-art embedding evaluations in low-resource NLP contexts. ## When NOT to use athina-evals - If open-source alternatives with transparent customization options are preferred over athina-evals' approach - In scenarios where API access requirements limit the ability to perform evaluations offline or in private environments ## When NOT to use mteb - Your project exclusively focuses on a single language or modality not covered by MTEB’s broad scope. - You need a tool that supports operations beyond evaluation, such as model training or fine-tuning directly within the same system. ## Common questions ### What is the difference between athina-evals and mteb? athina-evals: Python SDK for evaluating LLM generated responses. mteb: State-of-the-art evaluation of embeddings across languages and modalities. See the comparison table for live GitHub stats and shared categories. ### When should I choose athina-evals over mteb? Choose athina-evals over mteb when Tags unique to athina-evals: evaluation, evaluation-framework, evaluation-metrics, llm-eval; When comprehensive evaluation of LLM responses is required, leveraging athina's specific tools and metrics; Leaner open-issue backlog (3). ### When should I choose mteb over athina-evals? Choose mteb over athina-evals when Tags unique to mteb: benchmark, bitext-mining, clustering, embeddings; mteb ships Docker support for self-hosted deployment; You require benchmarking tools specifically designed for state-of-the-art embedding evaluations in low-resource NLP contexts. ### When should I avoid athina-evals? If open-source alternatives with transparent customization options are preferred over athina-evals' approach In scenarios where API access requirements limit the ability to perform evaluations offline or in private environments ### When should I avoid mteb? Your project exclusively focuses on a single language or modality not covered by MTEB’s broad scope. You need a tool that supports operations beyond evaluation, such as model training or fine-tuning directly within the same system. ### Is athina-evals or mteb more popular on GitHub? mteb has more GitHub stars (3,400 vs 301). Stars measure visibility, not whether either tool fits your constraints. ### Are athina-evals and mteb open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to athina-evals or mteb? GraphCanon lists graph-backed alternatives at [athina-evals alternatives](/tools/athina-ai-athina-evals/alternatives) and [mteb alternatives](/tools/embeddings-benchmark-mteb/alternatives) ([athina-evals markdown twin](/tools/athina-ai-athina-evals/alternatives.md), [mteb markdown twin](/tools/embeddings-benchmark-mteb/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/athina-ai-athina-evals-vs-embeddings-benchmark-mteb.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, athina-evals or mteb? athina-evals: Dormant. mteb: 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 athina-evals and mteb? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [athina-evals trust report](/tools/athina-ai-athina-evals/trust); [mteb trust report](/tools/embeddings-benchmark-mteb/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=athina-ai-athina-evals`](/api/graphcanon/graph?tool=athina-ai-athina-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/_