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Comparison

code-eval vs llm-course

Verdict

Pick code-eval when license: code-eval is MIT, llm-course is Apache-2.0; pick llm-course when license: llm-course is Apache-2.0, code-eval is MIT.

Markdown twin · code-eval alternatives · llm-course alternatives

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code-eval logo

code-eval

abacaj/code-eval

★ 429pushed Sep 12, 2023
vs
llm-course logo

llm-course

mlabonne/llm-course

★ 81kpushed Feb 5, 2026

Trust & integrity

Signalcode-evalllm-course
Maintenance
Dormant (1033d since push)
As of today · github_public_v1
Slowing (155d since push)
As of today · github_public_v1
Provenance
Not a fork · Personal account
As of today · github_public_v1
Not a fork · Personal account
As of today · github_public_v1
Security (OSV)
73 low (73 low)
As of today · osv@v1
No lockfile
As of today · none
code-eval trust reportllm-course trust reportTrust methodology

Tagline

code-eval
Run evaluation on LLMs using human-eval benchmark
llm-course
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

Stars

code-eval
429
llm-course
81k

Forks

code-eval
37
llm-course
9.4k

Open issues

code-eval
5
llm-course
84

Language

code-eval
Python
llm-course
-

Adopt for

code-eval
-
llm-course
The llm-course provides a comprehensive guided course on Large Language Models (LLMs), divided into three parts: LLM Fundamentals, The LLM Scientist, and The LLM Engineer. It includes resources such as Colab notebooks to

Persona

code-eval
-
llm-course
-

Runtime

code-eval
-
llm-course
-

License

code-eval
MIT
llm-course
Apache-2.0

Last pushed

code-eval
Sep 12, 2023
llm-course
Feb 5, 2026

Categories

code-eval
LLM Frameworks, Evaluation & Observability
llm-course
Model Training, LLM Frameworks, Evaluation & Observability, Inference & Serving

Trust and health

Maintenance

code-eval
Dormant (18%)
llm-course
Slowing (36%)

Days since push

code-eval
1033d
llm-course
155d

Open issues (now)

code-eval
5
llm-course
84

Security scan

code-eval
73 low (73 low)
llm-course
No lockfile

Full report

code-eval
Trust report
llm-course
Trust report

Shared compatibility

  • Python · code-eval: Python runtime · llm-course: Python runtime

Choose code-eval if…

  • License: code-eval is MIT, llm-course is Apache-2.0.
  • Tags unique to code-eval: wizardcoder, humaneval, python.
  • Leaner open-issue backlog (5).

When NOT to use code-eval

  • Last GitHub push was 1034 days ago (dormant maintenance, Sep 12, 2023). Validate activity before betting a new project on code-eval.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
  • Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
GitHubDetails

Choose llm-course if…

  • License: llm-course is Apache-2.0, code-eval is MIT.
  • Requirements: Course materials are available in Colab notebooks; access requires a Google account.
  • Tags unique to llm-course: colab-notebooks, machine-learning, course, large-language-models.
  • Also covers Model Training, Inference & Serving.
  • - When you want a comprehensive roadmap for understanding large language models including fundamental knowledge

When NOT to use llm-course

  • - If you only require a quick introduction to LLMs without deep dive into core components
  • - When you prefer working directly with commercial platforms that provide complete services rather than following detailed steps on building and deploying models yourself through this course's open,DI
GitHubDetails

Explore

code-eval trust report →llm-course trust report →LLM Frameworks category →Evaluation & Observability category →Model Training category →Inference & Serving 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 429 · llm-course 81k (synced Jul 11, 2026).

Common questions

What is the difference between code-eval and llm-course?
code-eval: Run evaluation on LLMs using human-eval benchmark. llm-course: Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.. See the comparison table for live GitHub stats and shared categories.
When should I choose code-eval over llm-course?
Choose code-eval over llm-course when License: code-eval is MIT, llm-course is Apache-2.0; Tags unique to code-eval: wizardcoder, humaneval, python; Leaner open-issue backlog (5).
When should I choose llm-course over code-eval?
Choose llm-course over code-eval when License: llm-course is Apache-2.0, code-eval is MIT; Requirements: Course materials are available in Colab notebooks; access requires a Google account; Tags unique to llm-course: colab-notebooks, machine-learning, course, large-language-models; Also covers Model Training, Inference & Serving; - When you want a comprehensive roadmap for understanding large language models including fundamental knowledge.
When should I avoid code-eval?
Last GitHub push was 1034 days ago (dormant maintenance, Sep 12, 2023). Validate activity before betting a new project on code-eval. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
When should I avoid llm-course?
- If you only require a quick introduction to LLMs without deep dive into core components - When you prefer working directly with commercial platforms that provide complete services rather than following detailed steps on building and deploying models yourself through this course's open,DI
Is code-eval or llm-course more popular on GitHub?
llm-course has more GitHub stars (80,839 vs 429). Stars measure visibility, not whether either tool fits your constraints.
Are code-eval and llm-course open source?
Yes - both are open-source projects on GitHub (code-eval: MIT, llm-course: Apache-2.0).
Where can I find alternatives to code-eval or llm-course?
GraphCanon lists graph-backed alternatives at code-eval alternatives and llm-course alternatives (code-eval markdown twin, llm-course 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 llm-course?
code-eval: Dormant. llm-course: Slowing. 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 llm-course?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: code-eval trust report; llm-course trust report.