Comparison
gpt4all vs StableLM
Verdict
Pick gpt4all if gPT4All is an open-source project designed to facilitate the local deployment of large language models (LLMs). It supports commercial usage with a permissive MIT license and is implemented in C++; pick StableLM if stableLM offers pre-trained language models for development and research with an emphasis on repeated-token training effects to improve performance.
Markdown twin · gpt4all alternatives · StableLM alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | gpt4all | StableLM |
|---|---|---|
| Maintenance | Dormant (453d since push) As of today · github_public_v1 | Dormant (844d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Organization account As of today · 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 |
Tagline
- gpt4all
- Run Local LLMs on Any Device
- StableLM
- Language models for development and research
Stars
- gpt4all
- 77k
- StableLM
- 16k
Forks
- gpt4all
- 8.3k
- StableLM
- 1.0k
Open issues
- gpt4all
- 772
- StableLM
- 28
Language
- gpt4all
- C++
- StableLM
- Jupyter Notebook
Adopt for
- gpt4all
- GPT4All is an open-source project designed to facilitate the local deployment of large language models (LLMs). It supports commercial usage with a permissive MIT license and is implemented in C++.
- StableLM
- StableLM offers pre-trained language models for development and research with an emphasis on repeated-token training effects to improve performance.
Persona
- gpt4all
- -
- StableLM
- -
Runtime
- gpt4all
- -
- StableLM
- -
License
- gpt4all
- MIT
- StableLM
- Apache-2.0
Last pushed
- gpt4all
- May 27, 2025
- StableLM
- Apr 8, 2024
Categories
- gpt4all
- Inference & Serving, LLM Frameworks
- StableLM
- LLM Frameworks
Trust and health
Days since push
- gpt4all
- 453d
- StableLM
- 844d
Open issues (now)
- gpt4all
- 772
- StableLM
- 28
Stars delta
- gpt4all
- -3 (30d)
- StableLM
- Unknown
Open issues delta
- gpt4all
- -1 (30d)
- StableLM
- Unknown
Full report
- gpt4all
- Trust report
- StableLM
- Trust report
Choose gpt4all if…
- gpt4all is primarily C++; StableLM is Jupyter Notebook.
- License: gpt4all is MIT, StableLM is Apache-2.0.
- Tags unique to gpt4all: ai-chat, llm-inference.
- Also covers Inference & Serving.
- - When you require on-device inference capabilities without reliance on cloud services.
When NOT to use gpt4all
- - In environments strictly requiring models supported by mainstream frameworks like TensorFlow or PyTorch, as GPT4All focuses on its standalone implementation.
- - When the project demands seamless integration with popular cloud infrastructures that don't align well with local deployments.
Choose StableLM if…
- StableLM is primarily Jupyter Notebook; gpt4all is C++.
- License: StableLM is Apache-2.0, gpt4all is MIT.
- Tags unique to StableLM: ai-research, language-models, model-training, open-source.
- When targeting research into the impact of multi-epoch token repetition on model performance, as StableLM is specifically designed around this concept.
When NOT to use StableLM
- If your project requires the strictest data privacy guarantees since some models are under less restrictive licenses, limiting their usage in projects with such constraints.
- For applications needing larger language models than 13 billion parameters, as StableLM's largest model is StableVicuna-13B.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (nomic-ai/gpt4all) · observed Aug 24, 2026
- GitHub forks (nomic-ai/gpt4all) · observed Aug 24, 2026
- Last push (nomic-ai/gpt4all) · observed May 27, 2025
- License file (MIT) · observed Aug 24, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (Stability-AI/StableLM) · observed Aug 1, 2026
- GitHub forks (Stability-AI/StableLM) · observed Aug 1, 2026
- Last push (Stability-AI/StableLM) · observed Apr 8, 2024
- License file (Apache-2.0) · observed Aug 1, 2026
- Decision facts (enrichment) · observed Jul 14, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: gpt4all 77k · StableLM 16k (synced Aug 24, 2026).
Common questions
- What is the difference between gpt4all and StableLM?
- gpt4all: Run Local LLMs on Any Device. StableLM: Language models for development and research. See the comparison table for live GitHub stats and shared categories.
- When should I choose gpt4all over StableLM?
- Choose gpt4all over StableLM when gpt4all is primarily C++; StableLM is Jupyter Notebook; License: gpt4all is MIT, StableLM is Apache-2.0; Tags unique to gpt4all: ai-chat, llm-inference; Also covers Inference & Serving; - When you require on-device inference capabilities without reliance on cloud services.
- When should I choose StableLM over gpt4all?
- Choose StableLM over gpt4all when StableLM is primarily Jupyter Notebook; gpt4all is C++; License: StableLM is Apache-2.0, gpt4all is MIT; Tags unique to StableLM: ai-research, language-models, model-training, open-source; When targeting research into the impact of multi-epoch token repetition on model performance, as StableLM is specifically designed around this concept.
- When should I avoid gpt4all?
- - In environments strictly requiring models supported by mainstream frameworks like TensorFlow or PyTorch, as GPT4All focuses on its standalone implementation. - When the project demands seamless integration with popular cloud infrastructures that don't align well with local deployments.
- When should I avoid StableLM?
- If your project requires the strictest data privacy guarantees since some models are under less restrictive licenses, limiting their usage in projects with such constraints. For applications needing larger language models than 13 billion parameters, as StableLM's largest model is StableVicuna-13B.
- Is gpt4all or StableLM more popular on GitHub?
- gpt4all has more GitHub stars (77,393 vs 15,684). Stars measure visibility, not whether either tool fits your constraints.
- Are gpt4all and StableLM open source?
- Yes - both are open-source projects on GitHub (gpt4all: MIT, StableLM: Apache-2.0).
- Where can I find alternatives to gpt4all or StableLM?
- GraphCanon lists graph-backed alternatives at gpt4all alternatives and StableLM alternatives (gpt4all 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, gpt4all or StableLM?
- gpt4all: Dormant. 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 gpt4all and StableLM?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: gpt4all trust report; StableLM trust report.