Home/Compare/jan vs ray-llm

Comparison

jan vs ray-llm

Verdict

Pick jan when tags unique to jan: chatgpt, gpt, llamacpp, localai; pick ray-llm when tags unique to ray-llm: llm-serving, ray.

Markdown twin · jan alternatives · ray-llm alternatives

GraphCanon updated today

jan logo

jan

janhq/jan

43kpushed Jul 10, 2026
vs
ray-llm logo

ray-llm

ray-project/ray-llm

1.3kpushed Mar 13, 2025

Trust & integrity

Signaljanray-llm
Maintenance
Very active (1d since push)
As of 1d · github_public_v1
Archived (485d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization account
As of 1d · github_public_v1
Not a fork · Organization account
As of today · github_public_v1
Security (OSV)
No lockfile
As of 1d · none
No lockfile
As of today · none

Tagline

jan
open source alternative to ChatGPT that runs offline locally
ray-llm
RayLLM - LLMs on Ray (Archived). Read README for more info.

Stars

jan
43k
ray-llm
1.3k

Forks

jan
2.9k
ray-llm
90

Open issues

jan
387
ray-llm
0

Language

jan
TypeScript
ray-llm
-

Adopt for

jan
Jan is a TypeScript-based, self-hosted chatbot application that acts as an offline alternative to services like ChatGPT.
ray-llm
-

Persona

jan
-
ray-llm
-

Runtime

jan
-
ray-llm
-

License

jan
Other
ray-llm
-

Last pushed

jan
Jul 10, 2026
ray-llm
Mar 13, 2025

Categories

jan
Inference & Serving, LLM Frameworks
ray-llm
Inference & Serving, LLM Frameworks

Trust and health

Maintenance

jan
Very active (96%)
ray-llm
Archived (8%)

Days since push

jan
1d
ray-llm
485d

Archived on GitHub

jan
No
ray-llm
Yes

Open issues (now)

jan
387
ray-llm
0

Full report

Choose jan if…

  • Tags unique to jan: chatgpt, gpt, llamacpp, localai.
  • - If you require an offline-capable AI assistant for environments without internet access.
  • More GitHub stars (43k vs 1.3k) - visibility, not fit.

When NOT to use jan

  • - If you require real-time updates to the AI model, since Jan uses static local models which may not get frequent updates.
  • - When a vast knowledge base or continuous learning capabilities are essential, as Jan's offline nature constrains its ability to stay current with new information.

Choose ray-llm if…

  • Tags unique to ray-llm: llm-serving, ray.
  • Leaner open-issue backlog (0).

When NOT to use ray-llm

  • ray-llm is archived on GitHub. Prefer an active alternative unless you maintain a private fork or need a frozen dependency.
  • Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.

Explore

Sources

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

GitHub stars on cards: jan 43k · ray-llm 1.3k (synced Jul 11, 2026).

Common questions

What is the difference between jan and ray-llm?
jan: open source alternative to ChatGPT that runs offline locally. ray-llm: RayLLM - LLMs on Ray (Archived). Read README for more info.. See the comparison table for live GitHub stats and shared categories.
When should I choose jan over ray-llm?
Choose jan over ray-llm when Tags unique to jan: chatgpt, gpt, llamacpp, localai; - If you require an offline-capable AI assistant for environments without internet access; More GitHub stars (43k vs 1.3k) - visibility, not fit.
When should I choose ray-llm over jan?
Choose ray-llm over jan when Tags unique to ray-llm: llm-serving, ray; Leaner open-issue backlog (0).
When should I avoid jan?
- If you require real-time updates to the AI model, since Jan uses static local models which may not get frequent updates. - When a vast knowledge base or continuous learning capabilities are essential, as Jan's offline nature constrains its ability to stay current with new information.
When should I avoid ray-llm?
ray-llm is archived on GitHub. Prefer an active alternative unless you maintain a private fork or need a frozen dependency. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
Is jan or ray-llm more popular on GitHub?
jan has more GitHub stars (43,499 vs 1,263). Stars measure visibility, not whether either tool fits your constraints.
Are jan and ray-llm open source?
Yes - both are open-source projects on GitHub.
Where can I find alternatives to jan or ray-llm?
GraphCanon lists graph-backed alternatives at jan alternatives and ray-llm alternatives (jan markdown twin, ray-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, jan or ray-llm?
jan: Very active. ray-llm: Archived. 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 jan and ray-llm?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: jan trust report; ray-llm trust report.