Home/Compare/cceval vs Awesome-Code-LLM

Comparison

cceval vs Awesome-Code-LLM

Verdict

Pick cceval if cceval is designed for assessing cross-file code completion capabilities in multilingual environments across different setups and retrieval methods; pick Awesome-Code-LLM if awesome-Code-LLM is a curated repository focused on code-focused large language models (code-LLMs), providing insights into top-performing models, evaluation toolkits, and research papers.

Markdown twin · cceval alternatives · Awesome-Code-LLM alternatives

GraphCanon updated 2w

cceval logo

cceval

amazon-science/cceval

182pushed Aug 15, 2025
vs
Awesome-Code-LLM logo

Awesome-Code-LLM

huybery/Awesome-Code-LLM

1.3kpushed Dec 10, 2024

Trust & integrity

SignalccevalAwesome-Code-LLM
Maintenance
Slowing (354d since push)
As of 2w · github_public_v1
Dormant (604d since push)
As of 2w · github_public_v1
Provenance
Not a fork · Organization account
As of 2w · github_public_v1
Not a fork · Personal account
As of 2w · github_public_v1
OSV dependency advisories
Published findings
As of 1mo · osv@v1
No lockfile (source not queried)
As of 1mo · 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

cceval
CrossCodeEval Benchmark for Cross-File Code Completion
Awesome-Code-LLM
👨💻 An awesome and curated list of best code-LLM for research.

Stars

cceval
182
Awesome-Code-LLM
1.3k

Forks

cceval
28
Awesome-Code-LLM
74

Open issues

cceval
5
Awesome-Code-LLM
4

Language

cceval
Python
Awesome-Code-LLM
-

Adopt for

cceval
cceval is designed for assessing cross-file code completion capabilities in multilingual environments across different setups and retrieval methods.
Awesome-Code-LLM
Awesome-Code-LLM is a curated repository focused on code-focused large language models (code-LLMs), providing insights into top-performing models, evaluation toolkits, and research papers.

Persona

cceval
-
Awesome-Code-LLM
-

Runtime

cceval
-
Awesome-Code-LLM
-

License

cceval
Apache-2.0
Awesome-Code-LLM
MIT License: Permissive open-source license that allows usage in virtually any project with little restrictions.

Last pushed

cceval
Aug 15, 2025
Awesome-Code-LLM
Dec 10, 2024

Categories

cceval
Evaluation & Observability
Awesome-Code-LLM
Evaluation & Observability, LLM Frameworks

Trust and health

Maintenance

cceval
Slowing (36%)
Awesome-Code-LLM
Dormant (18%)

Days since push

cceval
354d
Awesome-Code-LLM
604d

Open issues (now)

cceval
5
Awesome-Code-LLM
4

Owner type

cceval
Organization
Awesome-Code-LLM
User

OSV dependency advisories

cceval
Published findings
Awesome-Code-LLM
No lockfile (source not queried)

Full report

Awesome-Code-LLM
Trust report

Choose cceval if…

  • License: cceval is Apache-2.0, Awesome-Code-LLM is MIT.
  • Tags unique to cceval: benchmark, code-completion, cross-file, evaluation-tool.
  • You need to evaluate the performance of cross-file code completion systems that can handle multiple programming languages simultaneously

When NOT to use cceval

  • Your evaluation needs are focused solely on single-file or intralingual code completion benchmarks
  • You require real-time data access or live updates; cceval provides pre-packaged datasets that need to be manually obtained and uncompressed

Choose Awesome-Code-LLM if…

  • License: Awesome-Code-LLM is MIT, cceval is Apache-2.0.
  • Requirements: No specific requirements to use the repository for reference or evaluation, but contributions may involve technical knowledge and familiarity with code-LLMs..
  • Tags unique to Awesome-Code-LLM: awesome, code generation, large language models.
  • Also covers LLM Frameworks.
  • When you need a comprehensive list of state-of-the-art code generation LLMs with performance metrics such as HumanEval.

When NOT to use Awesome-Code-LLM

  • When looking for a tool that provides pre-trained models with built-in APIs or services, as Awesome-Code-LLM is primarily a directory/collection of information without direct service provision.
  • If you require real-time interactive use-cases and need immediate API access to LLMs; this repository does not offer such functionality.
  • In scenarios where you need a single end-to-end solution for training your own code generation models, as the platform is focused on aggregating third-party resources and research rather than offering

Explore

Sources

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

GitHub stars on cards: cceval 182 · Awesome-Code-LLM 1.3k (synced Aug 5, 2026).

Common questions

What is the difference between cceval and Awesome-Code-LLM?
cceval: CrossCodeEval Benchmark for Cross-File Code Completion. Awesome-Code-LLM: 👨💻 An awesome and curated list of best code-LLM for research.. See the comparison table for live GitHub stats and shared categories.
When should I choose cceval over Awesome-Code-LLM?
Choose cceval over Awesome-Code-LLM when License: cceval is Apache-2.0, Awesome-Code-LLM is MIT; Tags unique to cceval: benchmark, code-completion, cross-file, evaluation-tool; You need to evaluate the performance of cross-file code completion systems that can handle multiple programming languages simultaneously.
When should I choose Awesome-Code-LLM over cceval?
Choose Awesome-Code-LLM over cceval when License: Awesome-Code-LLM is MIT, cceval is Apache-2.0; Requirements: No specific requirements to use the repository for reference or evaluation, but contributions may involve technical knowledge and familiarity with code-LLMs.; Tags unique to Awesome-Code-LLM: awesome, code generation, large language models; Also covers LLM Frameworks; When you need a comprehensive list of state-of-the-art code generation LLMs with performance metrics such as HumanEval.
When should I avoid cceval?
Your evaluation needs are focused solely on single-file or intralingual code completion benchmarks You require real-time data access or live updates; cceval provides pre-packaged datasets that need to be manually obtained and uncompressed
When should I avoid Awesome-Code-LLM?
When looking for a tool that provides pre-trained models with built-in APIs or services, as Awesome-Code-LLM is primarily a directory/collection of information without direct service provision. If you require real-time interactive use-cases and need immediate API access to LLMs; this repository does not offer such functionality. In scenarios where you need a single end-to-end solution for training your own code generation models, as the platform is focused on aggregating third-party resources and research rather than offering
Is cceval or Awesome-Code-LLM more popular on GitHub?
Awesome-Code-LLM has more GitHub stars (1,291 vs 182). Stars measure visibility, not whether either tool fits your constraints.
Are cceval and Awesome-Code-LLM open source?
Yes - both are open-source projects on GitHub (cceval: Apache-2.0, Awesome-Code-LLM: MIT).
Where can I find alternatives to cceval or Awesome-Code-LLM?
GraphCanon lists graph-backed alternatives at cceval alternatives and Awesome-Code-LLM alternatives (cceval markdown twin, Awesome-Code-LLM 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, cceval or Awesome-Code-LLM?
cceval: Slowing. Awesome-Code-LLM: 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 cceval and Awesome-Code-LLM?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: cceval trust report; Awesome-Code-LLM trust report.

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