--- title: "bigcode-evaluation-harness vs VLMEvalKit" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/bigcode-project-bigcode-evaluation-harness-vs-open-compass-vlmevalkit" tools: ["bigcode-project-bigcode-evaluation-harness", "open-compass-vlmevalkit"] --- # bigcode-evaluation-harness vs VLMEvalKit *GraphCanon updated Aug 17, 2026* ## Verdict Pick bigcode-evaluation-harness if bigcode-evaluation-harness is tailored towards evaluating autoregressive code generation models via Python and Docker containers for secure and reproducible execution environments; 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. [bigcode-evaluation-harness](https://github.com/bigcode-project/bigcode-evaluation-harness) reports 1.1k GitHub stars, 261 forks, and 96 open issues, last pushed Jul 22, 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 [bigcode-evaluation-harness's repository](https://github.com/bigcode-project/bigcode-evaluation-harness) and [VLMEvalKit's repository](https://github.com/open-compass/VLMEvalKit). | | [bigcode-evaluation-harness](/tools/bigcode-project-bigcode-evaluation-harness.md) | [VLMEvalKit](/tools/open-compass-vlmevalkit.md) | | --- | --- | --- | | Tagline | A framework for evaluating autoregressive code generation language models. | An open-source evaluation toolkit for large vision-language models | | Stars | 1,055 | 4,345 | | Forks | 261 | 745 | | Open issues | 96 | 285 | | Language | Python | Python | | Adopt for | bigcode-evaluation-harness is tailored towards evaluating autoregressive code generation models via Python and Docker containers for secure and reproducible execution environments. | 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 | bigcode-evaluation-harness is distributed under the Apache-2.0 license. | Apache-2.0 | | Categories | Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [bigcode-evaluation-harness](/tools/bigcode-project-bigcode-evaluation-harness.md) | [VLMEvalKit](/tools/open-compass-vlmevalkit.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 378d | 0d | | Open issues (now) | 96 | 285 | | Stars delta | Unknown | +60 (30d) | | Open issues delta | Unknown | +21 (30d) | | Full report | [trust report](/tools/bigcode-project-bigcode-evaluation-harness/trust.md) | [trust report](/tools/open-compass-vlmevalkit/trust.md) | ## Decision facts: bigcode-evaluation-harness - **Requirements:** Users must have Docker installed to leverage the isolated execution environments for model output evaluation. - **Adopt for:** bigcode-evaluation-harness is tailored towards evaluating autoregressive code generation models via Python and Docker containers for secure and reproducible execution environments. - **License detail:** bigcode-evaluation-harness is distributed under the Apache-2.0 license. ## 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 bigcode-evaluation-harness if… - Requirements: Users must have Docker installed to leverage the isolated execution environments for model output evaluation.. - Tags unique to bigcode-evaluation-harness: autoregressive models, code generation, docker, python. - bigcode-evaluation-harness ships Docker support for self-hosted deployment. - When you need to isolate the evaluation environment from your local development setup, ensuring that no external variables affect the outcomes of model performance assessments. ### Choose VLMEvalKit if… - Tags unique to VLMEvalKit: computer-vision, evaluation, large language models, llm. - 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 1.1k) - visibility, not fit. ## When NOT to use bigcode-evaluation-harness - When you require real-time evaluation without the overhead of generating outputs locally and then evaluating them within isolated environments via Docker. - If your model's evaluation process does not necessitate autoregressive setup or the security features provided by Docker, using bigcode-evaluation-harness might introduce unnecessary complexity. ## 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 bigcode-evaluation-harness and VLMEvalKit? bigcode-evaluation-harness: A framework for evaluating autoregressive code generation language models.. 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 bigcode-evaluation-harness over VLMEvalKit? Choose bigcode-evaluation-harness over VLMEvalKit when Requirements: Users must have Docker installed to leverage the isolated execution environments for model output evaluation.; Tags unique to bigcode-evaluation-harness: autoregressive models, code generation, docker, python; bigcode-evaluation-harness ships Docker support for self-hosted deployment; When you need to isolate the evaluation environment from your local development setup, ensuring that no external variables affect the outcomes of model performance assessments. ### When should I choose VLMEvalKit over bigcode-evaluation-harness? Choose VLMEvalKit over bigcode-evaluation-harness when Tags unique to VLMEvalKit: computer-vision, evaluation, large language models, llm; 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 1.1k) - visibility, not fit. ### When should I avoid bigcode-evaluation-harness? When you require real-time evaluation without the overhead of generating outputs locally and then evaluating them within isolated environments via Docker. If your model's evaluation process does not necessitate autoregressive setup or the security features provided by Docker, using bigcode-evaluation-harness might introduce unnecessary complexity. ### 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 bigcode-evaluation-harness or VLMEvalKit more popular on GitHub? VLMEvalKit has more GitHub stars (4,345 vs 1,055). Stars measure visibility, not whether either tool fits your constraints. ### Are bigcode-evaluation-harness and VLMEvalKit open source? Yes - both are open-source projects on GitHub (bigcode-evaluation-harness: Apache-2.0, VLMEvalKit: Apache-2.0). ### Where can I find alternatives to bigcode-evaluation-harness or VLMEvalKit? GraphCanon lists graph-backed alternatives at [bigcode-evaluation-harness alternatives](/tools/bigcode-project-bigcode-evaluation-harness/alternatives) and [VLMEvalKit alternatives](/tools/open-compass-vlmevalkit/alternatives) ([bigcode-evaluation-harness markdown twin](/tools/bigcode-project-bigcode-evaluation-harness/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/bigcode-project-bigcode-evaluation-harness-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, bigcode-evaluation-harness or VLMEvalKit? bigcode-evaluation-harness: 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 bigcode-evaluation-harness and VLMEvalKit? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [bigcode-evaluation-harness trust report](/tools/bigcode-project-bigcode-evaluation-harness/trust); [VLMEvalKit trust report](/tools/open-compass-vlmevalkit/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=bigcode-project-bigcode-evaluation-harness`](/api/graphcanon/graph?tool=bigcode-project-bigcode-evaluation-harness) - 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/_