Comparison
judgeval vs evals
Verdict
Pick judgeval if judgeval is a Python tool that aids in the continuous improvement of AI agents through comprehensive environment data and evaluations, supporting methodologies like reinforcement learning and prompt engineering; pick evals if evals is an evaluation framework from OpenAI for assessing large language models and systems built with them. It includes an open-source registry of benchmarks and tools.
Markdown twin · judgeval alternatives · evals alternatives
GraphCanon updated Sep 20, 2026
10views this month
Trust & integrity
| Signal | judgeval | evals |
|---|---|---|
| Maintenance | Very active (4d since push) As of Sep 20, 2026 · github_public_v1 | Slowing (145d since push) As of Sep 7, 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 Sep 7, 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
- judgeval
- The Continuous-Improvement Stack for Agents
- evals
- Framework for evaluating LLMs and LLM systems with an open-source registry of benchmarks.
Stars
- judgeval
- 1.1k
- evals
- 19k
Forks
- judgeval
- 99
- evals
- 3.1k
Open issues
- judgeval
- 38
- evals
- 333
Language
- judgeval
- Python
- evals
- Python
Adopt for
- judgeval
- Judgeval is a Python tool that aids in the continuous improvement of AI agents through comprehensive environment data and evaluations, supporting methodologies like reinforcement learning and prompt engineering.
- evals
- Evals is an evaluation framework from OpenAI for assessing large language models and systems built with them. It includes an open-source registry of benchmarks and tools to create custom evaluations.
Persona
- judgeval
- -
- evals
- -
Runtime
- judgeval
- -
- evals
- -
License
- judgeval
- Apache-2.0
- evals
- Other
Last pushed
- judgeval
- Sep 16, 2026
- evals
- Apr 14, 2026
Categories
- judgeval
- AI Agents, Evaluation & Observability
- evals
- Evaluation & Observability
Trust and health
Maintenance
- judgeval
- Very active (96%)
- evals
- Slowing (36%)
Days since push
- judgeval
- 4d
- evals
- 145d
Open issues (now)
- judgeval
- 38
- evals
- 333
Stars delta
- judgeval
- +16 (30d)
- evals
- +271 (30d)
Open issues delta
- judgeval
- +10 (30d)
- evals
- +120 (30d)
Full report
- judgeval
- Trust report
- evals
- Trust report
Shared compatibility
- Python · judgeval: Python runtime · evals: Python runtime
Choose judgeval if…
- License: judgeval is Apache-2.0, evals is Other.
- Tags unique to judgeval: agent, agentic-ai, agents, grpo.
- Also covers AI Agents.
- You are working on an AI project where continuous monitoring and enhancement of your agent's performance are critical.
When NOT to use judgeval
- If you are looking for a tool focused solely on the theoretical aspects of AI development without practical, continuous improvement methodologies.
- You require a solution that only supports evaluation metrics and does not offer integrated environment data support, diverging from Judgeval’s comprehensive approach.
Choose evals if…
- License: evals is Other, judgeval is Apache-2.0.
- Tags unique to evals: benchmarking, custom eval creation, evaluation-framework, large-language-models.
- * When you need a comprehensive set of pre-existing evals and the ability to create your own tailored tests using specific use cases, especially within the OpenAI model ecosystem.
When NOT to use evals
- * When evaluating models or systems that do not benefit from being integrated with the OpenAI API, as some features like direct evals configuration in the OpenAI Dashboard require an OpenAI key.
- * If you are looking for an evaluation framework that doesn’t involve external dependencies such as Git Large File Storage (LFS) and specific Python version requirements (Python 3.9 minimum), or if a
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (JudgmentLabs/judgeval) · observed Sep 20, 2026
- GitHub forks (JudgmentLabs/judgeval) · observed Sep 20, 2026
- Last push (JudgmentLabs/judgeval) · observed Sep 16, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (openai/evals) · observed Sep 20, 2026
- GitHub forks (openai/evals) · observed Sep 20, 2026
- Last push (openai/evals) · observed Apr 14, 2026
- License file (Other) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: judgeval 1.1k · evals 19k (synced Sep 20, 2026).
Common questions
- What is the difference between judgeval and evals?
- judgeval: The Continuous-Improvement Stack for Agents. evals: Framework for evaluating LLMs and LLM systems with an open-source registry of benchmarks.. See the comparison table for live GitHub stats and shared categories.
- When should I choose judgeval over evals?
- Choose judgeval over evals when License: judgeval is Apache-2.0, evals is Other; Tags unique to judgeval: agent, agentic-ai, agents, grpo; Also covers AI Agents; You are working on an AI project where continuous monitoring and enhancement of your agent's performance are critical.
- When should I choose evals over judgeval?
- Choose evals over judgeval when License: evals is Other, judgeval is Apache-2.0; Tags unique to evals: benchmarking, custom eval creation, evaluation-framework, large-language-models; * When you need a comprehensive set of pre-existing evals and the ability to create your own tailored tests using specific use cases, especially within the OpenAI model ecosystem.
- When should I avoid judgeval?
- If you are looking for a tool focused solely on the theoretical aspects of AI development without practical, continuous improvement methodologies. You require a solution that only supports evaluation metrics and does not offer integrated environment data support, diverging from Judgeval’s comprehensive approach.
- When should I avoid evals?
- * When evaluating models or systems that do not benefit from being integrated with the OpenAI API, as some features like direct evals configuration in the OpenAI Dashboard require an OpenAI key. * If you are looking for an evaluation framework that doesn’t involve external dependencies such as Git Large File Storage (LFS) and specific Python version requirements (Python 3.9 minimum), or if a
- Is judgeval or evals more popular on GitHub?
- evals has more GitHub stars (19,398 vs 1,063). Stars measure visibility, not whether either tool fits your constraints.
- Are judgeval and evals open source?
- Yes - both are open-source projects on GitHub (judgeval: Apache-2.0, evals: Other).
- Where can I find alternatives to judgeval or evals?
- GraphCanon lists graph-backed alternatives at judgeval alternatives and evals alternatives (judgeval markdown twin, evals 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, judgeval or evals?
- judgeval: Very active. evals: Slowing. 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 judgeval and evals?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: judgeval trust report; evals trust report.