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Comparison

code-eval vs awesome-evals

Verdict

Pick code-eval if code-eval assesses large language models with the human-eval benchmark to provide insights into code generation reliability; pick awesome-evals if curated resources for AI agent evaluation with BenchFlow backing its maintenance.

Markdown twin · code-eval alternatives · awesome-evals alternatives

GraphCanon updated Oct 6, 2026

code-eval logo

code-eval

abacaj/code-eval

★ 432pushed Sep 12, 2023
vs
awesome-evals logo

awesome-evals

benchflow-ai/awesome-evals

★ 901pushed Sep 15, 2026

Trust & integrity

Signalcode-evalawesome-evals
Maintenance
Dormant (1120d since push)
As of Oct 6, 2026 · github_public_v1
Very active (4d since push)
As of Sep 20, 2026 · github_public_v1
Provenance
Not a fork · Personal account
As of Oct 6, 2026 · github_public_v1
Not a fork · Organization account
As of Sep 20, 2026 · github_public_v1
OSV dependency advisories
Published findings
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
code-eval trust reportawesome-evals trust reportTrust methodology

Tagline

code-eval
Run evaluation on LLMs using human-eval benchmark.
awesome-evals
A curated library of resources for building and evaluating AI agents

Stars

code-eval
432
awesome-evals
901

Forks

code-eval
36
awesome-evals
104

Open issues

code-eval
5
awesome-evals
34

Language

code-eval
Python
awesome-evals
-

Adopt for

code-eval
code-eval assesses large language models with the human-eval benchmark to provide insights into code generation reliability.
awesome-evals
Curated resources for AI agent evaluation with BenchFlow backing its maintenance

Persona

code-eval
-
awesome-evals
-

Runtime

code-eval
-
awesome-evals
-

License

code-eval
MIT
awesome-evals
Other

Last pushed

code-eval
Sep 12, 2023
awesome-evals
Sep 15, 2026

Categories

code-eval
Evaluation & Observability
awesome-evals
AI Agents, Evaluation & Observability

Trust and health

Maintenance

code-eval
Dormant (18%)
awesome-evals
Very active (96%)

Days since push

code-eval
1120d
awesome-evals
4d

Open issues (now)

code-eval
5
awesome-evals
34

Stars delta

code-eval
+1 (30d)
awesome-evals
+140 (30d)

Open issues delta

code-eval
0 (30d)
awesome-evals
+13 (30d)

Owner type

code-eval
User
awesome-evals
Organization

OSV dependency advisories

code-eval
Published findings
awesome-evals
No lockfile (source not queried)

Full report

code-eval
Trust report
awesome-evals
Trust report

Choose code-eval if…

  • License: code-eval is MIT, awesome-evals is Other.
  • Tags unique to code-eval: humaneval, wizardcoder.
  • When you need clear comparisons of pass rates for different LLMs using standardized tests

When NOT to use code-eval

  • If the tool's results do not correlate well with the official published benchmarks due to unknown prompt differences
  • For real-time or dynamic evaluations as this repo offers pre-computed static results only
GitHubDetails

Choose awesome-evals if…

  • License: awesome-evals is Other, code-eval is MIT.
  • Tags unique to awesome-evals: agent-evaluation, ai-agents, awesome-list, benchmarks.
  • Also covers AI Agents.
  • Need diverse resources encompassing papers, blogs, talks, tools, and benchmarks specifically curated for AI agent evaluation

When NOT to use awesome-evals

  • Require real-time interactive support or direct tool integrations not covered by a static resource list
  • Seeking proprietary tools from specific vendors rather than open resources and community content
GitHubDetails

Explore

code-eval trust report →awesome-evals trust report →Evaluation & Observability category →AI Agents 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: code-eval 432 · awesome-evals 901 (synced Oct 6, 2026).

Common questions

What is the difference between code-eval and awesome-evals?
code-eval: Run evaluation on LLMs using human-eval benchmark.. awesome-evals: A curated library of resources for building and evaluating AI agents. See the comparison table for live GitHub stats and shared categories.
When should I choose code-eval over awesome-evals?
Choose code-eval over awesome-evals when License: code-eval is MIT, awesome-evals is Other; Tags unique to code-eval: humaneval, wizardcoder; When you need clear comparisons of pass rates for different LLMs using standardized tests.
When should I choose awesome-evals over code-eval?
Choose awesome-evals over code-eval when License: awesome-evals is Other, code-eval is MIT; Tags unique to awesome-evals: agent-evaluation, ai-agents, awesome-list, benchmarks; Also covers AI Agents; Need diverse resources encompassing papers, blogs, talks, tools, and benchmarks specifically curated for AI agent evaluation.
When should I avoid code-eval?
If the tool's results do not correlate well with the official published benchmarks due to unknown prompt differences For real-time or dynamic evaluations as this repo offers pre-computed static results only
When should I avoid awesome-evals?
Require real-time interactive support or direct tool integrations not covered by a static resource list Seeking proprietary tools from specific vendors rather than open resources and community content
Is code-eval or awesome-evals more popular on GitHub?
awesome-evals has more GitHub stars (901 vs 432). Stars measure visibility, not whether either tool fits your constraints.
Are code-eval and awesome-evals open source?
Yes - both are open-source projects on GitHub (code-eval: MIT, awesome-evals: Other).
Where can I find alternatives to code-eval or awesome-evals?
GraphCanon lists graph-backed alternatives at code-eval alternatives and awesome-evals alternatives (code-eval markdown twin, awesome-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, code-eval or awesome-evals?
code-eval: Dormant. awesome-evals: 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 code-eval and awesome-evals?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: code-eval trust report; awesome-evals trust report.

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