Comparison
litgpt vs ray-llm
Verdict
Pick litgpt if litgpt offers a suite of over 20 high-performance large language models, with tools for pretraining, finetuning, and deployment at scale, all under the Apache-2.0 license; pick ray-llm if ray-LLM is an archived project for deploying large language models on Ray, with its functionalities now integrated into the Ray framework through the ray.serve.llm and ray.data.llm APIs.
Markdown twin · litgpt alternatives · ray-llm alternatives
GraphCanon updated Sep 20, 2026
14views this month
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Trust & integrity
| Signal | litgpt | ray-llm |
|---|---|---|
| Maintenance | Very active (3d since push) As of Sep 18, 2026 · github_public_v1 | Archived (554d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Sep 18, 2026 · osv@v1 | No lockfile (source not queried) As of Sep 18, 2026 · 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 |
Tagline
- litgpt
- High-performance LLMs for pretraining, finetuning, and deployment
- ray-llm
- Archived repository for LLMs on Ray, now integrated into Ray.
Stars
- litgpt
- 14k
- ray-llm
- 1.3k
Forks
- litgpt
- 1.5k
- ray-llm
- 90
Open issues
- litgpt
- 290
- ray-llm
- 0
Language
- litgpt
- Python
- ray-llm
- -
Adopt for
- litgpt
- litgpt offers a suite of over 20 high-performance large language models, with tools for pretraining, finetuning, and deployment at scale, all under the Apache-2.0 license.
- ray-llm
- Ray-LLM is an archived project for deploying large language models on Ray, with its functionalities now integrated into the Ray framework through the ray.serve.llm and ray.data.llm APIs.
Persona
- litgpt
- -
- ray-llm
- -
Runtime
- litgpt
- -
- ray-llm
- -
License
- litgpt
- Apache-2.0
- ray-llm
- License information is not provided.
Last pushed
- litgpt
- Sep 14, 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
- Very active (96%)
- ray-llm
- Archived (8%)
Days since push
- litgpt
- 3d
- ray-llm
- 554d
Archived on GitHub
- litgpt
- No
- ray-llm
- Yes
Open issues (now)
- litgpt
- 290
- ray-llm
- 0
Stars delta
- litgpt
- +62 (30d)
- ray-llm
- 0 (30d)
Open issues delta
- litgpt
- +18 (30d)
- ray-llm
- 0 (30d)
Full report
- litgpt
- Trust report
- ray-llm
- Trust report
Choose litgpt if…
- Tags unique to litgpt: ai, artificial-intelligence, deep-learning, large-language-models.
- Also covers LLM Frameworks.
- When you need a comprehensive set of over 20 high-performance LLMs for pretraining, finetuning, and deployment.
When NOT to use litgpt
- If you are looking for a tool that supports languages other than Python, as litgpt is exclusively Python-based.
- When you need a tool that offers fewer model options, as litgpt provides over 20 models which might be overwhelming for specific use cases.
- If you require proprietary licensing, as litgpt is open-source under the Apache-2.0 license.
Choose ray-llm if…
- Pricing: Pricing details are not available..
- Requirements: Ensure you have the latest version of Ray installed to use the ray.serve.llm and ray.data.llm APIs..
- Tags unique to ray-llm: llm-serving, ray.
- If you are working with Ray and need to deploy large language models, use the ray.serve.llm and ray.data.llm APIs, which are now integrated into the Ray framework.
When NOT to use ray-llm
- Do not use the archived Ray-LLM repository for active development or deployment, as it is no longer maintained and its functionalities have been integrated into the Ray framework.
- If you require the latest features and support for deploying large language models, avoid the archived repository and use the ray.serve.llm and ray.data.llm APIs directly.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (Lightning-AI/litgpt) · observed Sep 20, 2026
- GitHub forks (Lightning-AI/litgpt) · observed Sep 20, 2026
- Last push (Lightning-AI/litgpt) · observed Sep 14, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
- GitHub stars (ray-project/ray-llm) · observed Sep 20, 2026
- GitHub forks (ray-project/ray-llm) · observed Sep 20, 2026
- Last push (ray-project/ray-llm) · observed Mar 13, 2025
- License file (unknown) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
GitHub stars on cards: litgpt 14k · ray-llm 1.3k (synced Sep 20, 2026).
Common questions
- What is the difference between litgpt and ray-llm?
- litgpt: High-performance LLMs for pretraining, finetuning, and deployment. ray-llm: Archived repository for LLMs on Ray, now integrated into Ray.. 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 Tags unique to litgpt: ai, artificial-intelligence, deep-learning, large-language-models; Also covers LLM Frameworks; When you need a comprehensive set of over 20 high-performance LLMs for pretraining, finetuning, and deployment.
- When should I choose ray-llm over litgpt?
- Choose ray-llm over litgpt when Pricing: Pricing details are not available.; Requirements: Ensure you have the latest version of Ray installed to use the ray.serve.llm and ray.data.llm APIs.; Tags unique to ray-llm: llm-serving, ray; If you are working with Ray and need to deploy large language models, use the ray.serve.llm and ray.data.llm APIs, which are now integrated into the Ray framework.
- When should I avoid litgpt?
- If you are looking for a tool that supports languages other than Python, as litgpt is exclusively Python-based. When you need a tool that offers fewer model options, as litgpt provides over 20 models which might be overwhelming for specific use cases. If you require proprietary licensing, as litgpt is open-source under the Apache-2.0 license.
- When should I avoid ray-llm?
- Do not use the archived Ray-LLM repository for active development or deployment, as it is no longer maintained and its functionalities have been integrated into the Ray framework. If you require the latest features and support for deploying large language models, avoid the archived repository and use the ray.serve.llm and ray.data.llm APIs directly.
- Is litgpt or ray-llm more popular on GitHub?
- litgpt has more GitHub stars (13,667 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: 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 litgpt and ray-llm?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: litgpt trust report; ray-llm trust report.