Comparison
litgpt vs SPIN
Verdict
Pick litgpt if litGPT offers extensive support for high-performance LLMs with comprehensive workflows for pretraining, fine-tuning, and deployment; pick SPIN if sPIN is specialized for self-play fine-tuning in large language models through deep learning.
Markdown twin · litgpt alternatives · SPIN alternatives
GraphCanon updated today
Trust & integrity
| Signal | litgpt | SPIN |
|---|---|---|
| Maintenance | Active (17d since push) As of 2w · github_public_v1 | Dormant (837d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Personal account As of today · 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 |
Tagline
- litgpt
- High-performance LLMs with recipes for pretraining, finetuning and deployment
- SPIN
- Official implementation of Self-Play Fine-Tuning
Stars
- litgpt
- 14k
- SPIN
- 1.3k
Forks
- litgpt
- 1.5k
- SPIN
- 106
Open issues
- litgpt
- 272
- SPIN
- 24
Language
- litgpt
- Python
- SPIN
- Python
Adopt for
- litgpt
- LitGPT offers extensive support for high-performance LLMs with comprehensive workflows for pretraining, fine-tuning, and deployment.
- SPIN
- SPIN is specialized for self-play fine-tuning in large language models through deep learning.
Persona
- litgpt
- -
- SPIN
- -
Runtime
- litgpt
- -
- SPIN
- -
License
- litgpt
- LitGPT operates under the open-source Apache-2.0 license, providing permissive terms for use and modification.
- SPIN
- Apache-2.0
Last pushed
- litgpt
- Jul 20, 2026
- SPIN
- May 8, 2024
Categories
- litgpt
- Inference & Serving, LLM Frameworks, Model Training
- SPIN
- LLM Frameworks, Model Training
Trust and health
Maintenance
- litgpt
- Active (82%)
- SPIN
- Dormant (18%)
Days since push
- litgpt
- 17d
- SPIN
- 837d
Open issues (now)
- litgpt
- 272
- SPIN
- 24
Stars delta
- litgpt
- +137 (30d)
- SPIN
- +6 (30d)
Open issues delta
- litgpt
- +6 (30d)
- SPIN
- 0 (30d)
Owner type
- litgpt
- Organization
- SPIN
- User
Full report
- litgpt
- Trust report
- SPIN
- 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, llm-inference, llms.
- Also covers Inference & Serving.
- 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.
Choose SPIN if…
- Tags unique to SPIN: fine-tuning, self-play.
- When implementing self-play algorithms aimed at enhancing performance of large language models within constrained domains.
- Leaner open-issue backlog (24).
When NOT to use SPIN
- If your project strictly adheres to frameworks that do not incorporate self-play techniques for training or fine-tuning models.
- When prioritizing a model training framework that relies on supervised learning rather than the self-play methodology SPIN is based upon.
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 Aug 7, 2026
- GitHub forks (Lightning-AI/litgpt) · observed Aug 7, 2026
- Last push (Lightning-AI/litgpt) · observed Jul 20, 2026
- License file (Apache-2.0) · observed Aug 7, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (uclaml/SPIN) · observed Aug 24, 2026
- GitHub forks (uclaml/SPIN) · observed Aug 24, 2026
- Last push (uclaml/SPIN) · observed May 8, 2024
- License file (Apache-2.0) · observed Aug 24, 2026
- Decision facts (enrichment) · observed Jul 14, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: litgpt 14k · SPIN 1.3k (synced Aug 7, 2026).
Common questions
- What is the difference between litgpt and SPIN?
- litgpt: High-performance LLMs with recipes for pretraining, finetuning and deployment. SPIN: Official implementation of Self-Play Fine-Tuning. See the comparison table for live GitHub stats and shared categories.
- When should I choose litgpt over SPIN?
- Choose litgpt over SPIN 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, llm-inference, llms; Also covers Inference & Serving; 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 SPIN over litgpt?
- Choose SPIN over litgpt when Tags unique to SPIN: fine-tuning, self-play; When implementing self-play algorithms aimed at enhancing performance of large language models within constrained domains; Leaner open-issue backlog (24).
- 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 SPIN?
- If your project strictly adheres to frameworks that do not incorporate self-play techniques for training or fine-tuning models. When prioritizing a model training framework that relies on supervised learning rather than the self-play methodology SPIN is based upon.
- Is litgpt or SPIN more popular on GitHub?
- litgpt has more GitHub stars (13,605 vs 1,254). Stars measure visibility, not whether either tool fits your constraints.
- Are litgpt and SPIN open source?
- Yes - both are open-source projects on GitHub (litgpt: Apache-2.0, SPIN: Apache-2.0).
- Where can I find alternatives to litgpt or SPIN?
- GraphCanon lists graph-backed alternatives at litgpt alternatives and SPIN alternatives (litgpt markdown twin, SPIN 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 SPIN?
- litgpt: Active. SPIN: Dormant. 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 SPIN?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: litgpt trust report; SPIN trust report.