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Comparison

litgpt vs ray-llm

Verdict

Pick litgpt if litGPT offers extensive support for high-performance LLMs with comprehensive workflows for pretraining, fine-tuning, and deployment; pick ray-llm if archived LLM deployment tool integrated into Ray; now focus on built-in APIs (`ray.serve.llm` & `ray.data.llm`).

Markdown twin · litgpt alternatives · ray-llm alternatives

GraphCanon updated 2w

litgpt logo

litgpt

Lightning-AI/litgpt

★ 14kpushed Jul 20, 2026
vs
ray-llm logo

ray-llm

ray-project/ray-llm

★ 1.3kpushed Mar 13, 2025

Trust & integrity

Signallitgptray-llm
Maintenance
Active (17d since push)
As of 2w · github_public_v1
Archived (507d since push)
As of 3w · github_public_v1
Provenance
Not a fork · Organization account
As of 2w · github_public_v1
Not a fork · Organization account
As of 3w · 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
litgpt trust reportray-llm trust reportTrust methodology

Tagline

litgpt
High-performance LLMs with recipes for pretraining, finetuning and deployment
ray-llm
Archived repository; LLM serving APIs integrated into the Ray project

Stars

litgpt
14k
ray-llm
1.3k

Forks

litgpt
1.5k
ray-llm
90

Open issues

litgpt
272
ray-llm
0

Language

litgpt
Python
ray-llm
-

Adopt for

litgpt
LitGPT offers extensive support for high-performance LLMs with comprehensive workflows for pretraining, fine-tuning, and deployment.
ray-llm
Archived LLM deployment tool integrated into Ray; now focus on built-in APIs (`ray.serve.llm` & `ray.data.llm`).

Persona

litgpt
-
ray-llm
-

Runtime

litgpt
-
ray-llm
-

License

litgpt
LitGPT operates under the open-source Apache-2.0 license, providing permissive terms for use and modification.
ray-llm
-

Last pushed

litgpt
Jul 20, 2026
ray-llm
Mar 13, 2025

Categories

litgpt
Inference & Serving, LLM Frameworks, Model Training
ray-llm
Inference & Serving, Model Training

Trust and health

Maintenance

litgpt
Active (82%)
ray-llm
Archived (8%)

Days since push

litgpt
17d
ray-llm
507d

Archived on GitHub

litgpt
No
ray-llm
Yes

Open issues (now)

litgpt
272
ray-llm
0

Stars delta

litgpt
+137 (30d)
ray-llm
Unknown

Open issues delta

litgpt
+6 (30d)
ray-llm
Unknown

Full report

litgpt
Trust report
ray-llm
Trust report

Choose litgpt if…

  • Pricing: The core LitGPT framework is free to use under an open source license, but users might encounter costs when deploying at scale or using high-performance models..
  • Requirements: Min 16 GB RAM.
  • Tags unique to litgpt: ai, artificial-intelligence, deep-learning, large language models.
  • Also covers LLM Frameworks.
  • If you are focusing on a project that requires rapid prototyping or experimentation with over 20 different LLMs to find the best fit for your application.

When NOT to use litgpt

  • If you need a tool specifically optimized for resource-constrained devices, as LitGPT focuses on high-performance LLMs and may require more resources.
  • When your project is strictly limited to only one or two types of specific LLMs; in this case, another specialized framework that caters narrowly might be preferable.
GitHubDetails

Choose ray-llm if…

  • Tags unique to ray-llm: llm-serving, ray.
  • For deploying LLMs with new Ray-integrated APIs, ensuring direct support and updates from the Ray team.
  • Leaner open-issue backlog (0).

When NOT to use ray-llm

  • If seeking a standalone solution distinct from Ray’s main project, preferring specialized tools.
  • For needs requiring active maintenance and development in this specific repository; consider alternative up-to-date projects.
GitHubDetails

Explore

litgpt trust report →ray-llm trust report →Inference & Serving category →LLM Frameworks category →Model Training 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: litgpt 14k · ray-llm 1.3k (synced Aug 7, 2026).

Common questions

What is the difference between litgpt and ray-llm?
litgpt: High-performance LLMs with recipes for pretraining, finetuning and deployment. ray-llm: Archived repository; LLM serving APIs integrated into the Ray project. See the comparison table for live GitHub stats and shared categories.
When should I choose litgpt over ray-llm?
Choose litgpt over ray-llm when Pricing: The core LitGPT framework is free to use under an open source license, but users might encounter costs when deploying at scale or using high-performance models.; Requirements: Min 16 GB RAM; Tags unique to litgpt: ai, artificial-intelligence, deep-learning, large language models; Also covers LLM Frameworks; If you are focusing on a project that requires rapid prototyping or experimentation with over 20 different LLMs to find the best fit for your application.
When should I choose ray-llm over litgpt?
Choose ray-llm over litgpt when Tags unique to ray-llm: llm-serving, ray; For deploying LLMs with new Ray-integrated APIs, ensuring direct support and updates from the Ray team; Leaner open-issue backlog (0).
When should I avoid litgpt?
If you need a tool specifically optimized for resource-constrained devices, as LitGPT focuses on high-performance LLMs and may require more resources. When your project is strictly limited to only one or two types of specific LLMs; in this case, another specialized framework that caters narrowly might be preferable.
When should I avoid ray-llm?
If seeking a standalone solution distinct from Ray’s main project, preferring specialized tools. For needs requiring active maintenance and development in this specific repository; consider alternative up-to-date projects.
Is litgpt or ray-llm more popular on GitHub?
litgpt has more GitHub stars (13,605 vs 1,261). Stars measure visibility, not whether either tool fits your constraints.
Are litgpt and ray-llm open source?
Yes - both are open-source projects on GitHub.
Where can I find alternatives to litgpt or ray-llm?
GraphCanon lists graph-backed alternatives at litgpt alternatives and ray-llm alternatives (litgpt 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, litgpt or ray-llm?
litgpt: 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 litgpt and ray-llm?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: litgpt trust report; ray-llm trust report.

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