Home/Compare/deepeval vs evals

Comparison

deepeval vs evals

Verdict

Pick deepeval when license: deepeval is Apache-2.0, evals is Other; pick evals when license: evals is Other, deepeval is Apache-2.0.

Markdown twin · deepeval alternatives · evals alternatives

GraphCanon updated today

deepeval logo

deepeval

confident-ai/deepeval

17kpushed Jul 10, 2026
vs
evals logo

evals

openai/evals

19kpushed Apr 14, 2026

Trust & integrity

Signaldeepevalevals
Maintenance
Very active (0d since push)
As of today · github_public_v1
Steady (87d since push)
As of 1d · github_public_v1
Provenance
Not a fork · Organization account
As of today · github_public_v1
Not a fork · Organization account
As of 1d · github_public_v1
Security (OSV)
No lockfile
As of today · none
No lockfile
As of 1d · none

Tagline

deepeval
The LLM Evaluation Framework
evals
Framework for evaluating LLMs and LLM systems with an open-source registry of benchmarks.

Stars

deepeval
17k
evals
19k

Forks

deepeval
1.6k
evals
3.0k

Open issues

deepeval
334
evals
217

Language

deepeval
Python
evals
Python

Adopt for

deepeval
-
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

deepeval
-
evals
-

Runtime

deepeval
-
evals
-

License

deepeval
Apache-2.0
evals
Other

Last pushed

deepeval
Jul 10, 2026
evals
Apr 14, 2026

Categories

deepeval
Evaluation & Observability, LLM Frameworks
evals
Evaluation & Observability

Trust and health

Maintenance

deepeval
Very active (96%)
evals
Steady (60%)

Days since push

deepeval
0d
evals
87d

Open issues (now)

deepeval
334
evals
217

Full report

deepeval
Trust report

Choose deepeval if…

  • License: deepeval is Apache-2.0, evals is Other.
  • Tags unique to deepeval: evaluation-metrics, llm-evaluation, llm-evaluation-framework, llm-evaluation-metrics.
  • Also covers LLM Frameworks.

When NOT to use deepeval

  • Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.

Choose evals if…

  • License: evals is Other, deepeval is Apache-2.0.
  • Tags unique to evals: benchmarking, custom eval creation, large-language-models, llm systems.
  • * 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繁

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: deepeval 17k · evals 19k (synced Jul 11, 2026).

Common questions

What is the difference between deepeval and evals?
deepeval: The LLM Evaluation Framework. 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 deepeval over evals?
Choose deepeval over evals when License: deepeval is Apache-2.0, evals is Other; Tags unique to deepeval: evaluation-metrics, llm-evaluation, llm-evaluation-framework, llm-evaluation-metrics; Also covers LLM Frameworks.
When should I choose evals over deepeval?
Choose evals over deepeval when License: evals is Other, deepeval is Apache-2.0; Tags unique to evals: benchmarking, custom eval creation, large-language-models, llm systems; * 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 deepeval?
Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
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繁
Is deepeval or evals more popular on GitHub?
evals has more GitHub stars (18,890 vs 16,767). Stars measure visibility, not whether either tool fits your constraints.
Are deepeval and evals open source?
Yes - both are open-source projects on GitHub (deepeval: Apache-2.0, evals: Other).
Where can I find alternatives to deepeval or evals?
GraphCanon lists graph-backed alternatives at deepeval alternatives and evals alternatives (deepeval 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, deepeval or evals?
deepeval: Very active. evals: Steady. 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 evals?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: deepeval trust report; evals trust report.