Comparison
deepeval vs lmms-eval
Verdict
Pick deepeval if deepeval is a Python-based framework designed for evaluating large language models with an array of metrics and evaluation methodologies; pick lmms-eval if lmms-eval is a one-stop solution for benchmarking multimodal large language models across various tasks including text, image, video, and audio.
Markdown twin · deepeval alternatives · lmms-eval alternatives
GraphCanon updated Sep 20, 2026
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Trust & integrity
| Signal | deepeval | lmms-eval |
|---|---|---|
| Maintenance | Very active (1d since push) As of Sep 20, 2026 · github_public_v1 | Active (11d since push) As of Aug 17, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 | Not a fork · Organization account As of Aug 17, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- deepeval
- LLM Evaluation Framework.
- lmms-eval
- One-for-All Multimodal Evaluation Toolkit Across Text, Image, Video, and Audio Tasks
Stars
- deepeval
- 18k
- lmms-eval
- 4.4k
Forks
- deepeval
- 2.0k
- lmms-eval
- 639
Open issues
- deepeval
- 624
- lmms-eval
- 49
Language
- deepeval
- Python
- lmms-eval
- Python
Adopt for
- deepeval
- Deepeval is a Python-based framework designed for evaluating large language models with an array of metrics and evaluation methodologies.
- lmms-eval
- lmms-eval is a one-stop solution for benchmarking multimodal large language models across various tasks including text, image, video, and audio.
Persona
- deepeval
- -
- lmms-eval
- -
Runtime
- deepeval
- -
- lmms-eval
- -
License
- deepeval
- Apache-2.0 License
- lmms-eval
- Other
Last pushed
- deepeval
- Sep 18, 2026
- lmms-eval
- Aug 6, 2026
Categories
- deepeval
- Evaluation & Observability
- lmms-eval
- Evaluation & Observability
Trust and health
Maintenance
- deepeval
- Very active (96%)
- lmms-eval
- Active (82%)
Days since push
- deepeval
- 1d
- lmms-eval
- 11d
Open issues (now)
- deepeval
- 624
- lmms-eval
- 49
Stars delta
- deepeval
- +1.1k (30d)
- lmms-eval
- +52 (30d)
Open issues delta
- deepeval
- +220 (30d)
- lmms-eval
- +9 (30d)
Full report
- deepeval
- Trust report
- lmms-eval
- Trust report
Shared compatibility
- Python · deepeval: Python runtime · lmms-eval: Python runtime
Choose deepeval if…
- License: deepeval is Apache-2.0, lmms-eval is Other.
- Requirements: Requires Python environment and familiarity with large language models to effectively utilize Deepeval's capabilities..
- Tags unique to deepeval: metrics.
- When developing large language models and you need a comprehensive evaluation framework to measure their performance across various metrics.
When NOT to use deepeval
- For small-scale applications that do not require the depth of metrics and evaluations offered by Deepeval, as it might be overkill.
- In situations where there is a need for real-time performance monitoring, since Deepeval focuses more on post-development evaluation rather than continuous runtime analysis.
Choose lmms-eval if…
- License: lmms-eval is Other, deepeval is Apache-2.0.
- Tags unique to lmms-eval: agi, audio-evaluation, benchmark, large-language-models.
- You need to evaluate LLaVA series models on different datasets with precise control over reproducibility details like torch/cuda versions.
When NOT to use lmms-eval
- Looking for a tool that supports less than Python 3.12, as uv setup mandates this version.
- Requiring support beyond text, image, video, and audio modalities which lmms-eval specifically covers.
- Your project doesn't benefit from extensive results tracking in Google Sheets or relies solely on alternative reproducibility mechanisms without external dependencies.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (confident-ai/deepeval) · observed Sep 20, 2026
- GitHub forks (confident-ai/deepeval) · observed Sep 20, 2026
- Last push (confident-ai/deepeval) · observed Sep 18, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (EvolvingLMMs-Lab/lmms-eval) · observed Sep 20, 2026
- GitHub forks (EvolvingLMMs-Lab/lmms-eval) · observed Sep 20, 2026
- Last push (EvolvingLMMs-Lab/lmms-eval) · observed Aug 6, 2026
- License file (Other) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: deepeval 18k · lmms-eval 4.4k (synced Sep 20, 2026).
Common questions
- What is the difference between deepeval and lmms-eval?
- deepeval: LLM Evaluation Framework.. lmms-eval: One-for-All Multimodal Evaluation Toolkit Across Text, Image, Video, and Audio Tasks. See the comparison table for live GitHub stats and shared categories.
- When should I choose deepeval over lmms-eval?
- Choose deepeval over lmms-eval when License: deepeval is Apache-2.0, lmms-eval is Other; Requirements: Requires Python environment and familiarity with large language models to effectively utilize Deepeval's capabilities.; Tags unique to deepeval: metrics; When developing large language models and you need a comprehensive evaluation framework to measure their performance across various metrics.
- When should I choose lmms-eval over deepeval?
- Choose lmms-eval over deepeval when License: lmms-eval is Other, deepeval is Apache-2.0; Tags unique to lmms-eval: agi, audio-evaluation, benchmark, large-language-models; You need to evaluate LLaVA series models on different datasets with precise control over reproducibility details like torch/cuda versions.
- When should I avoid deepeval?
- For small-scale applications that do not require the depth of metrics and evaluations offered by Deepeval, as it might be overkill. In situations where there is a need for real-time performance monitoring, since Deepeval focuses more on post-development evaluation rather than continuous runtime analysis.
- When should I avoid lmms-eval?
- Looking for a tool that supports less than Python 3.12, as uv setup mandates this version. Requiring support beyond text, image, video, and audio modalities which lmms-eval specifically covers. Your project doesn't benefit from extensive results tracking in Google Sheets or relies solely on alternative reproducibility mechanisms without external dependencies.
- Is deepeval or lmms-eval more popular on GitHub?
- deepeval has more GitHub stars (18,342 vs 4,368). Stars measure visibility, not whether either tool fits your constraints.
- Are deepeval and lmms-eval open source?
- Yes - both are open-source projects on GitHub (deepeval: Apache-2.0, lmms-eval: Other).
- Where can I find alternatives to deepeval or lmms-eval?
- GraphCanon lists graph-backed alternatives at deepeval alternatives and lmms-eval alternatives (deepeval markdown twin, lmms-eval markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, deepeval or lmms-eval?
- deepeval: Very active. lmms-eval: 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 deepeval and lmms-eval?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: deepeval trust report; lmms-eval trust report.