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Comparison

rag-time vs llm-course

Verdict

Pick rag-time when license: rag-time is MIT, llm-course is Apache-2.0; pick llm-course when license: llm-course is Apache-2.0, rag-time is MIT.

Markdown twin · rag-time alternatives · llm-course alternatives

GraphCanon updated today

rag-time logo

rag-time

microsoft/rag-time

★ 894pushed Jun 17, 2025
vs
llm-course logo

llm-course

mlabonne/llm-course

★ 81kpushed Feb 5, 2026

Trust & integrity

Signalrag-timellm-course
Maintenance
Dormant (388d since push)
As of today · github_public_v1
Slowing (155d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization account
As of today · github_public_v1
Not a fork · Personal account
As of today · github_public_v1
Security (OSV)
No lockfile
As of today · none
No lockfile
As of today · none
rag-time trust reportllm-course trust reportTrust methodology

Tagline

rag-time
RAG Time: A 5-week Learning Journey to Mastering RAG
llm-course
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

Stars

rag-time
894
llm-course
81k

Forks

rag-time
316
llm-course
9.4k

Open issues

rag-time
4
llm-course
84

Language

rag-time
Jupyter Notebook
llm-course
-

Adopt for

rag-time
-
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

rag-time
-
llm-course
-

Runtime

rag-time
-
llm-course
-

License

rag-time
MIT
llm-course
Apache-2.0

Last pushed

rag-time
Jun 17, 2025
llm-course
Feb 5, 2026

Categories

rag-time
LLM Frameworks, Vector Databases, Inference & Serving
llm-course
LLM Frameworks, Model Training, Evaluation & Observability, Inference & Serving

Trust and health

Maintenance

rag-time
Dormant (18%)
llm-course
Slowing (36%)

Days since push

rag-time
388d
llm-course
155d

Open issues (now)

rag-time
4
llm-course
84

Owner type

rag-time
Organization
llm-course
User

Full report

rag-time
Trust report
llm-course
Trust report

Choose rag-time if…

  • License: rag-time is MIT, llm-course is Apache-2.0.
  • Tags unique to rag-time: ai, binary-quantization, generative-ai, gpt.
  • Also covers Vector Databases.

When NOT to use rag-time

  • Last GitHub push was 389 days ago (dormant maintenance, Jun 17, 2025). Validate activity before betting a new project on rag-time.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
  • Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
  • Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
GitHubDetails

Choose llm-course if…

  • License: llm-course is Apache-2.0, rag-time 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, Evaluation & Observability.
  • - 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

rag-time trust report →llm-course trust report →LLM Frameworks category →Vector Databases category →Inference & Serving category →Model Training category →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: rag-time 894 · llm-course 81k (synced Jul 11, 2026).

Common questions

What is the difference between rag-time and llm-course?
rag-time: RAG Time: A 5-week Learning Journey to Mastering RAG. 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 rag-time over llm-course?
Choose rag-time over llm-course when License: rag-time is MIT, llm-course is Apache-2.0; Tags unique to rag-time: ai, binary-quantization, generative-ai, gpt; Also covers Vector Databases.
When should I choose llm-course over rag-time?
Choose llm-course over rag-time when License: llm-course is Apache-2.0, rag-time 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, Evaluation & Observability; - When you want a comprehensive roadmap for understanding large language models including fundamental knowledge.
When should I avoid rag-time?
Last GitHub push was 389 days ago (dormant maintenance, Jun 17, 2025). Validate activity before betting a new project on rag-time. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
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 rag-time or llm-course more popular on GitHub?
llm-course has more GitHub stars (80,839 vs 894). Stars measure visibility, not whether either tool fits your constraints.
Are rag-time and llm-course open source?
Yes - both are open-source projects on GitHub (rag-time: MIT, llm-course: Apache-2.0).
Where can I find alternatives to rag-time or llm-course?
GraphCanon lists graph-backed alternatives at rag-time alternatives and llm-course alternatives (rag-time 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, rag-time or llm-course?
rag-time: 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 rag-time and llm-course?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: rag-time trust report; llm-course trust report.