--- title: "athina-evals vs VLMEvalKit" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/athina-ai-athina-evals-vs-open-compass-vlmevalkit" tools: ["athina-ai-athina-evals", "open-compass-vlmevalkit"] --- # athina-evals vs VLMEvalKit *GraphCanon updated Aug 17, 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 VLMEvalKit if vLMEvalKit is an open-source Python evaluation toolkit for large vision-language models that offers one-command evaluation with support for various benchmarks and models. [athina-evals](https://docs.athina.ai) reports 301 GitHub stars, 22 forks, and 3 open issues, last pushed Jun 6, 2025. [VLMEvalKit](https://huggingface.co/spaces/opencompass/open_vlm_leaderboard) has 4.3k stars, 745 forks, and 285 open issues, last pushed Aug 17, 2026. Figures are from public GitHub metadata via [athina-evals's repository](https://github.com/athina-ai/athina-evals) and [VLMEvalKit's repository](https://github.com/open-compass/VLMEvalKit). | | [athina-evals](/tools/athina-ai-athina-evals.md) | [VLMEvalKit](/tools/open-compass-vlmevalkit.md) | | --- | --- | --- | | Tagline | Python SDK for evaluating LLM generated responses | An open-source evaluation toolkit for large vision-language models | | Stars | 301 | 4,345 | | Forks | 22 | 745 | | Open issues | 3 | 285 | | 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. | VLMEvalKit is an open-source Python evaluation toolkit for large vision-language models that offers one-command evaluation with support for various benchmarks and models. | | 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) | [VLMEvalKit](/tools/open-compass-vlmevalkit.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 417d | 0d | | Open issues (now) | 3 | 285 | | Stars delta | Unknown | +60 (30d) | | Open issues delta | Unknown | +21 (30d) | | Full report | [trust report](/tools/athina-ai-athina-evals/trust.md) | [trust report](/tools/open-compass-vlmevalkit/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: VLMEvalKit - **Adopt for:** VLMEvalKit is an open-source Python evaluation toolkit for large vision-language models that offers one-command evaluation with support for various benchmarks and models. ## Choose when ### Choose athina-evals if… - Tags unique to athina-evals: evaluation-framework, evaluation-metrics, llm-eval, llm-evaluation. - When comprehensive evaluation of LLM responses is required, leveraging athina's specific tools and metrics - Leaner open-issue backlog (3). ### Choose VLMEvalKit if… - Tags unique to VLMEvalKit: computer-vision, large language models, llm, multi-modal. - When you need to evaluate models supporting thinking mode, as it provides a custom split_thinking function improving accuracy. - More GitHub stars (4.3k vs 301) - visibility, not fit. ## 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 VLMEvalKit - If your project requires evaluation tools that generate Excel files with individual cells larger than the default support of 32,767 characters and cannot switch to TSV format. - When you do not need generation-based evaluation methods with exact matching and LLM-based answer extraction. ## Common questions ### What is the difference between athina-evals and VLMEvalKit? athina-evals: Python SDK for evaluating LLM generated responses. VLMEvalKit: An open-source evaluation toolkit for large vision-language models. See the comparison table for live GitHub stats and shared categories. ### When should I choose athina-evals over VLMEvalKit? Choose athina-evals over VLMEvalKit when Tags unique to athina-evals: evaluation-framework, evaluation-metrics, llm-eval, llm-evaluation; When comprehensive evaluation of LLM responses is required, leveraging athina's specific tools and metrics; Leaner open-issue backlog (3). ### When should I choose VLMEvalKit over athina-evals? Choose VLMEvalKit over athina-evals when Tags unique to VLMEvalKit: computer-vision, large language models, llm, multi-modal; When you need to evaluate models supporting thinking mode, as it provides a custom split_thinking function improving accuracy; More GitHub stars (4.3k vs 301) - visibility, not fit. ### 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 VLMEvalKit? If your project requires evaluation tools that generate Excel files with individual cells larger than the default support of 32,767 characters and cannot switch to TSV format. When you do not need generation-based evaluation methods with exact matching and LLM-based answer extraction. ### Is athina-evals or VLMEvalKit more popular on GitHub? VLMEvalKit has more GitHub stars (4,345 vs 301). Stars measure visibility, not whether either tool fits your constraints. ### Are athina-evals and VLMEvalKit open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to athina-evals or VLMEvalKit? GraphCanon lists graph-backed alternatives at [athina-evals alternatives](/tools/athina-ai-athina-evals/alternatives) and [VLMEvalKit alternatives](/tools/open-compass-vlmevalkit/alternatives) ([athina-evals markdown twin](/tools/athina-ai-athina-evals/alternatives.md), [VLMEvalKit markdown twin](/tools/open-compass-vlmevalkit/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-open-compass-vlmevalkit.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, athina-evals or VLMEvalKit? athina-evals: Dormant. VLMEvalKit: 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 VLMEvalKit? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [athina-evals trust report](/tools/athina-ai-athina-evals/trust); [VLMEvalKit trust report](/tools/open-compass-vlmevalkit/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/_