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Comparison

evals vs ARES

Verdict

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 to create custom evaluations; pick ARES if aRES is a Python-based tool for automated evaluation of RAG systems, offering scoring and comparison functionalities.

Markdown twin · evals alternatives · ARES alternatives

GraphCanon updated Sep 20, 2026

9views this month

evals logo

evals

openai/evals

★ 19kpushed Apr 14, 2026
vs
ARES logo

ARES

stanford-futuredata/ARES

★ 733pushed Mar 28, 2025

Trust & integrity

SignalevalsARES
Maintenance
Slowing (145d since push)
As of Sep 7, 2026 · github_public_v1
Dormant (538d since push)
As of Sep 18, 2026 · github_public_v1
Provenance
Not a fork · Organization account
As of Sep 7, 2026 · github_public_v1
Not a fork · Organization account
As of Sep 18, 2026 · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of Jul 11, 2026 · osv@v1
Published findings
As of Sep 18, 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
evals trust reportARES trust reportTrust methodology

Tagline

evals
Framework for evaluating LLMs and LLM systems with an open-source registry of benchmarks.
ARES
Automated Evaluation of RAG Systems

Stars

evals
19k
ARES
733

Forks

evals
3.1k
ARES
67

Open issues

evals
333
ARES
22

Language

evals
Python
ARES
Python

Adopt for

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.
ARES
ARES is a Python-based tool for automated evaluation of RAG systems, offering scoring and comparison functionalities.

Persona

evals
-
ARES
-

Runtime

evals
-
ARES
-

License

evals
Other
ARES
Apache-2.0

Last pushed

evals
Apr 14, 2026
ARES
Mar 28, 2025

Categories

evals
Evaluation & Observability
ARES
Evaluation & Observability

Trust and health

Maintenance

evals
Slowing (36%)
ARES
Dormant (18%)

Days since push

evals
145d
ARES
538d

Open issues (now)

evals
333
ARES
22

Stars delta

evals
+271 (30d)
ARES
+2 (30d)

Open issues delta

evals
+120 (30d)
ARES
+1 (30d)

OSV dependency advisories

evals
No lockfile (source not queried)
ARES
Published findings

Full report

evals
Trust report
ARES
Trust report

Shared compatibility

  • OpenAI API · evals: OpenAI API · ARES: OpenAI API
  • Python · evals: Python runtime · ARES: Python runtime

Choose evals if…

  • License: evals is Other, ARES 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
GitHubDetails

Choose ARES if…

  • License: ARES is Apache-2.0, evals is Other.
  • Requirements: Requires over 100 GB of available disk space and a compatible GPU like the A100.; Installation of conda and gcc is necessary for setup..
  • Tags unique to ARES: api integration, automated evaluation, comparison, evaluation criteria.
  • Use ARES when you need to evaluate RAG systems with specific criteria such as context relevance, answer faithfulness, and answer relevance.

When NOT to use ARES

  • Do not use ARES if you lack the necessary human-annotated datasets for evaluation criteria or if you do not have a large set of unlabeled triples for scoring.
  • Avoid ARES if your machine does not meet the requirements, such as having over 100 GB of available disk space and a compatible GPU like the A100.
  • Do not use ARES if you cannot set up the required environment, including conda and gcc, on your machine.
GitHubDetails

Explore

evals trust report →ARES trust report →Evaluation & Observability category →All comparisonsStack workflowsTrending tools

Sources

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

GitHub stars on cards: evals 19k · ARES 733 (synced Sep 20, 2026).

Common questions

What is the difference between evals and ARES?
evals: Framework for evaluating LLMs and LLM systems with an open-source registry of benchmarks.. ARES: Automated Evaluation of RAG Systems. See the comparison table for live GitHub stats and shared categories.
When should I choose evals over ARES?
Choose evals over ARES when License: evals is Other, ARES 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 choose ARES over evals?
Choose ARES over evals when License: ARES is Apache-2.0, evals is Other; Requirements: Requires over 100 GB of available disk space and a compatible GPU like the A100.; Installation of conda and gcc is necessary for setup.; Tags unique to ARES: api integration, automated evaluation, comparison, evaluation criteria; Use ARES when you need to evaluate RAG systems with specific criteria such as context relevance, answer faithfulness, and answer relevance.
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
When should I avoid ARES?
Do not use ARES if you lack the necessary human-annotated datasets for evaluation criteria or if you do not have a large set of unlabeled triples for scoring. Avoid ARES if your machine does not meet the requirements, such as having over 100 GB of available disk space and a compatible GPU like the A100. Do not use ARES if you cannot set up the required environment, including conda and gcc, on your machine.
Is evals or ARES more popular on GitHub?
evals has more GitHub stars (19,398 vs 733). Stars measure visibility, not whether either tool fits your constraints.
Are evals and ARES open source?
Yes - both are open-source projects on GitHub (evals: Other, ARES: Apache-2.0).
Where can I find alternatives to evals or ARES?
GraphCanon lists graph-backed alternatives at evals alternatives and ARES alternatives (evals markdown twin, ARES 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, evals or ARES?
evals: Slowing. ARES: Dormant. 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 evals and ARES?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: evals trust report; ARES trust report.

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