--- title: "mteb vs autoarena" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/embeddings-benchmark-mteb-vs-kolenaio-autoarena" tools: ["embeddings-benchmark-mteb", "kolenaio-autoarena"] --- # mteb vs autoarena *GraphCanon updated Aug 22, 2026* ## Verdict Pick mteb if mTEB is an evaluator for embedding models across languages and modalities under the Apache-2.0 license; pick autoarena if autoarena automates evaluations for LLMs and RAG systems through a user-friendly interface where projects are created and judged without manual intervention by the users. [mteb](https://docs.mteb.org) reports 3.4k GitHub stars, 670 forks, and 340 open issues, last pushed Aug 21, 2026. [autoarena](https://www.kolena.com/autoarena/) has 108 stars, 9 forks, and 4 open issues, last pushed Dec 16, 2024. Figures are from public GitHub metadata via [mteb's repository](https://github.com/embeddings-benchmark/mteb) and [autoarena's repository](https://github.com/kolenaIO/autoarena). | | [mteb](/tools/embeddings-benchmark-mteb.md) | [autoarena](/tools/kolenaio-autoarena.md) | | --- | --- | --- | | Tagline | State-of-the-art evaluation of embeddings across languages and modalities | Automated evaluation of LLMs and RAG systems | | Stars | 3,400 | 108 | | Forks | 670 | 9 | | Open issues | 340 | 4 | | Language | Python | TypeScript | | Adopt for | MTEB is an evaluator for embedding models across languages and modalities under the Apache-2.0 license. | autoarena automates evaluations for LLMs and RAG systems through a user-friendly interface where projects are created and judged without manual intervention by the users. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 license | | Categories | Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [mteb](/tools/embeddings-benchmark-mteb.md) | [autoarena](/tools/kolenaio-autoarena.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 0d | 589d | | Open issues (now) | 340 | 4 | | Stars delta | +36 (30d) | Unknown | | Open issues delta | +31 (30d) | Unknown | | Full report | [trust report](/tools/embeddings-benchmark-mteb/trust.md) | [trust report](/tools/kolenaio-autoarena/trust.md) | ## Shared compatibility - **Python**: [mteb](/tools/embeddings-benchmark-mteb.md) - Python runtime; [autoarena](/tools/kolenaio-autoarena.md) - Python runtime ## Decision facts: mteb - **Adopt for:** MTEB is an evaluator for embedding models across languages and modalities under the Apache-2.0 license. ## Decision facts: autoarena - **Hosting:** self hosted - **Requirements:** Python environment and internet access are needed for PyPI installation via pip. - **Adopt for:** autoarena automates evaluations for LLMs and RAG systems through a user-friendly interface where projects are created and judged without manual intervention by the users. - **License detail:** Apache-2.0 license ## Choose when ### Choose mteb if… - mteb is primarily Python; autoarena is TypeScript. - 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. ### Choose autoarena if… - autoarena is primarily TypeScript; mteb is Python. - Requirements: Python environment and internet access are needed for PyPI installation via pip.. - Tags unique to autoarena: ai, evaluation, llm-evaluation, rag. - When you need a TypeScript-based tool to rank LLMs and RAG systems via automated head-to-head comparisons, and a web UI is preferable. ## 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. ## When NOT to use autoarena - If your environment lacks the necessary Python packages or you cannot install from PyPI due to restrictions. - When real-time evaluation needs surpass capabilities, such as requiring immediate feedback beyond autoarena's batch-processing approach. ## Common questions ### What is the difference between mteb and autoarena? mteb: State-of-the-art evaluation of embeddings across languages and modalities. autoarena: Automated evaluation of LLMs and RAG systems. See the comparison table for live GitHub stats and shared categories. ### When should I choose mteb over autoarena? Choose mteb over autoarena when mteb is primarily Python; autoarena is TypeScript; 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 choose autoarena over mteb? Choose autoarena over mteb when autoarena is primarily TypeScript; mteb is Python; Requirements: Python environment and internet access are needed for PyPI installation via pip.; Tags unique to autoarena: ai, evaluation, llm-evaluation, rag; When you need a TypeScript-based tool to rank LLMs and RAG systems via automated head-to-head comparisons, and a web UI is preferable. ### 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. ### When should I avoid autoarena? If your environment lacks the necessary Python packages or you cannot install from PyPI due to restrictions. When real-time evaluation needs surpass capabilities, such as requiring immediate feedback beyond autoarena's batch-processing approach. ### Is mteb or autoarena more popular on GitHub? mteb has more GitHub stars (3,400 vs 108). Stars measure visibility, not whether either tool fits your constraints. ### Are mteb and autoarena open source? Yes - both are open-source projects on GitHub (mteb: Apache-2.0, autoarena: Apache-2.0). ### Where can I find alternatives to mteb or autoarena? GraphCanon lists graph-backed alternatives at [mteb alternatives](/tools/embeddings-benchmark-mteb/alternatives) and [autoarena alternatives](/tools/kolenaio-autoarena/alternatives) ([mteb markdown twin](/tools/embeddings-benchmark-mteb/alternatives.md), [autoarena markdown twin](/tools/kolenaio-autoarena/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-kolenaio-autoarena.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, mteb or autoarena? mteb: Very active. autoarena: Dormant. 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 autoarena? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [mteb trust report](/tools/embeddings-benchmark-mteb/trust); [autoarena trust report](/tools/kolenaio-autoarena/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/_