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Home/Compare/Awesome-Code-LLM vs DevEval

Comparison

Awesome-Code-LLM vs DevEval

Verdict

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; pick DevEval if devEval suits organizations requiring Python-centric software development benchmarks and practices evaluation.

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

GraphCanon updated 2w

Awesome-Code-LLM logo

Awesome-Code-LLM

huybery/Awesome-Code-LLM

★ 1.3kpushed Dec 10, 2024
vs
DevEval logo

DevEval

open-compass/DevEval

★ 138pushed May 30, 2024

Trust & integrity

SignalAwesome-Code-LLMDevEval
Maintenance
Dormant (604d since push)
As of 2w · github_public_v1
Dormant (797d since push)
As of 2w · github_public_v1
Provenance
Not a fork · Personal account
As of 2w · github_public_v1
Not a fork · Organization account
As of 2w · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
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
Awesome-Code-LLM trust reportDevEval trust reportTrust methodology

Tagline

Awesome-Code-LLM
👨💻 An awesome and curated list of best code-LLM for research.
DevEval
A Comprehensive Benchmark for Software Development

Stars

Awesome-Code-LLM
1.3k
DevEval
138

Forks

Awesome-Code-LLM
74
DevEval
13

Open issues

Awesome-Code-LLM
4
DevEval
0

Language

Awesome-Code-LLM
-
DevEval
Python

Adopt for

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.
DevEval
DevEval suits organizations requiring Python-centric software development benchmarks and practices evaluation.

Persona

Awesome-Code-LLM
-
DevEval
-

Runtime

Awesome-Code-LLM
-
DevEval
-

License

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

Last pushed

Awesome-Code-LLM
Dec 10, 2024
DevEval
May 30, 2024

Categories

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

Trust and health

Days since push

Awesome-Code-LLM
604d
DevEval
797d

Open issues (now)

Awesome-Code-LLM
4
DevEval
0

Owner type

Awesome-Code-LLM
User
DevEval
Organization

Full report

Awesome-Code-LLM
Trust report
DevEval
Trust report

Choose Awesome-Code-LLM if…

  • License: Awesome-Code-LLM is MIT, DevEval 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
GitHubDetails

Choose DevEval if…

  • License: DevEval is Apache-2.0, Awesome-Code-LLM is MIT.
  • Tags unique to DevEval: benchmark, docker-supported, python, software-development.
  • Choose DevEval when you require comprehensive benchmarking specifically for software development using Python.

When NOT to use DevEval

  • Avoid DevEval if your software projects heavily rely on languages other than Python.
  • Do not use it when a non-Dockerized evaluation tool is preferred due to organizational constraints or preferences.
GitHubDetails

Explore

Awesome-Code-LLM trust report →DevEval trust report →Evaluation & Observability category →LLM Frameworks 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: Awesome-Code-LLM 1.3k · DevEval 138 (synced Aug 6, 2026).

Common questions

What is the difference between Awesome-Code-LLM and DevEval?
Awesome-Code-LLM: 👨💻 An awesome and curated list of best code-LLM for research.. DevEval: A Comprehensive Benchmark for Software Development. See the comparison table for live GitHub stats and shared categories.
When should I choose Awesome-Code-LLM over DevEval?
Choose Awesome-Code-LLM over DevEval when License: Awesome-Code-LLM is MIT, DevEval 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 choose DevEval over Awesome-Code-LLM?
Choose DevEval over Awesome-Code-LLM when License: DevEval is Apache-2.0, Awesome-Code-LLM is MIT; Tags unique to DevEval: benchmark, docker-supported, python, software-development; Choose DevEval when you require comprehensive benchmarking specifically for software development using Python.
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
When should I avoid DevEval?
Avoid DevEval if your software projects heavily rely on languages other than Python. Do not use it when a non-Dockerized evaluation tool is preferred due to organizational constraints or preferences.
Is Awesome-Code-LLM or DevEval more popular on GitHub?
Awesome-Code-LLM has more GitHub stars (1,291 vs 138). Stars measure visibility, not whether either tool fits your constraints.
Are Awesome-Code-LLM and DevEval open source?
Yes - both are open-source projects on GitHub (Awesome-Code-LLM: MIT, DevEval: Apache-2.0).
Where can I find alternatives to Awesome-Code-LLM or DevEval?
GraphCanon lists graph-backed alternatives at Awesome-Code-LLM alternatives and DevEval alternatives (Awesome-Code-LLM markdown twin, DevEval 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, Awesome-Code-LLM or DevEval?
Awesome-Code-LLM: Dormant. DevEval: 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 Awesome-Code-LLM and DevEval?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Awesome-Code-LLM trust report; DevEval trust report.

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