Comparison
litgpt vs StableLM
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 StableLM if stableLM is a series of language models from Stability AI, featuring models like StableLM-3B-4E1T, which is a 3 billion parameter model trained on 4 trillion tokens over 4 epochs.
Markdown twin · litgpt alternatives · StableLM alternatives
GraphCanon updated Sep 20, 2026
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Trust & integrity
| Signal | litgpt | StableLM |
|---|---|---|
| Maintenance | Very active (3d since push) As of Sep 18, 2026 · github_public_v1 | Dormant (892d 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
- StableLM
- Stability AI Language Models
Stars
- litgpt
- 14k
- StableLM
- 16k
Forks
- litgpt
- 1.5k
- StableLM
- 1.0k
Open issues
- litgpt
- 290
- StableLM
- 27
Language
- litgpt
- Python
- StableLM
- Jupyter Notebook
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.
- StableLM
- StableLM is a series of language models from Stability AI, featuring models like StableLM-3B-4E1T, which is a 3 billion parameter model trained on 4 trillion tokens over 4 epochs. The repository includes model updates, a
Persona
- litgpt
- -
- StableLM
- -
Runtime
- litgpt
- -
- StableLM
- -
License
- litgpt
- Apache-2.0
- StableLM
- Apache-2.0
Last pushed
- litgpt
- Sep 14, 2026
- StableLM
- Apr 8, 2024
Categories
- litgpt
- Inference & Serving, LLM Frameworks, Model Training
- StableLM
- LLM Frameworks, Model Training
Trust and health
Maintenance
- litgpt
- Very active (96%)
- StableLM
- Dormant (18%)
Days since push
- litgpt
- 3d
- StableLM
- 892d
Open issues (now)
- litgpt
- 290
- StableLM
- 27
Stars delta
- litgpt
- +62 (30d)
- StableLM
- -6 (30d)
Open issues delta
- litgpt
- +18 (30d)
- StableLM
- -1 (30d)
Full report
- litgpt
- Trust report
- StableLM
- Trust report
Choose litgpt if…
- litgpt is primarily Python; StableLM is Jupyter Notebook.
- Tags unique to litgpt: ai, artificial-intelligence, deep-learning, large-language-models.
- Also covers Inference & Serving.
- 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 StableLM if…
- StableLM is primarily Jupyter Notebook; litgpt is Python.
- Tags unique to StableLM: checkpoints, fine-tuning, language models, pre-training.
- When you need a model that has been trained with a multi-epoch regime to study the impact of repeated tokens on performance, such as the StableLM-3B-4E1T model.
When NOT to use StableLM
- If you need a model that is strictly under the Apache-2.0 license, as StableLM models are available under different licenses like CC BY-SA-4.0 and CC BY-NC-SA-4.0.
- When you require a model that has not been trained with repeated tokens, as StableLM models like StableLM-3B-4E1T are specifically designed with this training method.
- If your project requires a model that is not a decoder-only transformer with specific architecture modifications, such as the use of Rotary Position Embeddings.
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 (Stability-AI/StableLM) · observed Sep 20, 2026
- GitHub forks (Stability-AI/StableLM) · observed Sep 20, 2026
- Last push (Stability-AI/StableLM) · observed Apr 8, 2024
- 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 on cards: litgpt 14k · StableLM 16k (synced Sep 20, 2026).
Common questions
- What is the difference between litgpt and StableLM?
- litgpt: High-performance LLMs for pretraining, finetuning, and deployment. StableLM: Stability AI Language Models. See the comparison table for live GitHub stats and shared categories.
- When should I choose litgpt over StableLM?
- Choose litgpt over StableLM when litgpt is primarily Python; StableLM is Jupyter Notebook; Tags unique to litgpt: ai, artificial-intelligence, deep-learning, large-language-models; Also covers Inference & Serving; When you need a comprehensive set of over 20 high-performance LLMs for pretraining, finetuning, and deployment.
- When should I choose StableLM over litgpt?
- Choose StableLM over litgpt when StableLM is primarily Jupyter Notebook; litgpt is Python; Tags unique to StableLM: checkpoints, fine-tuning, language models, pre-training; When you need a model that has been trained with a multi-epoch regime to study the impact of repeated tokens on performance, such as the StableLM-3B-4E1T model.
- 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 StableLM?
- If you need a model that is strictly under the Apache-2.0 license, as StableLM models are available under different licenses like CC BY-SA-4.0 and CC BY-NC-SA-4.0. When you require a model that has not been trained with repeated tokens, as StableLM models like StableLM-3B-4E1T are specifically designed with this training method. If your project requires a model that is not a decoder-only transformer with specific architecture modifications, such as the use of Rotary Position Embeddings.
- Is litgpt or StableLM more popular on GitHub?
- StableLM has more GitHub stars (15,678 vs 13,667). Stars measure visibility, not whether either tool fits your constraints.
- Are litgpt and StableLM open source?
- Yes - both are open-source projects on GitHub (litgpt: Apache-2.0, StableLM: Apache-2.0).
- Where can I find alternatives to litgpt or StableLM?
- GraphCanon lists graph-backed alternatives at litgpt alternatives and StableLM alternatives (litgpt markdown twin, StableLM 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 StableLM?
- litgpt: Very active. StableLM: 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 StableLM?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: litgpt trust report; StableLM trust report.