Comparison
StableLM vs awesome-LLM-resources
Verdict
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. The repository includes model updates, a; pick awesome-LLM-resources if awesome-LLM-resources is a curated list of resources related to large language models, covering a wide range of topics from.
Markdown twin · StableLM alternatives · awesome-LLM-resources alternatives
GraphCanon updated Sep 20, 2026
15views this month
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Trust & integrity
| Signal | StableLM | awesome-LLM-resources |
|---|---|---|
| Maintenance | Dormant (892d since push) As of Sep 18, 2026 · github_public_v1 | Very active (3d 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 · Personal 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
- StableLM
- Stability AI Language Models
- awesome-LLM-resources
- Summary of the world's best LLM resources.
Stars
- StableLM
- 16k
- awesome-LLM-resources
- 9.0k
Forks
- StableLM
- 1.0k
- awesome-LLM-resources
- 993
Open issues
- StableLM
- 27
- awesome-LLM-resources
- 40
Language
- StableLM
- Jupyter Notebook
- awesome-LLM-resources
- -
Adopt for
- 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
- awesome-LLM-resources
- awesome-LLM-resources is a curated list of resources related to large language models, covering a wide range of topics from multimodal generation to model training and inference.
Persona
- StableLM
- -
- awesome-LLM-resources
- -
Runtime
- StableLM
- -
- awesome-LLM-resources
- -
License
- StableLM
- Apache-2.0
- awesome-LLM-resources
- The repository is licensed under Apache-2.0, allowing for free use, modification, and distribution.
Last pushed
- StableLM
- Apr 8, 2024
- awesome-LLM-resources
- Sep 14, 2026
Categories
- StableLM
- LLM Frameworks, Model Training
- awesome-LLM-resources
- AI Agents, Computer Vision, Data & Retrieval, Developer Tools, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training
Trust and health
Maintenance
- StableLM
- Dormant (18%)
- awesome-LLM-resources
- Very active (96%)
Days since push
- StableLM
- 892d
- awesome-LLM-resources
- 3d
Open issues (now)
- StableLM
- 27
- awesome-LLM-resources
- 40
Stars delta
- StableLM
- -6 (30d)
- awesome-LLM-resources
- +123 (30d)
Open issues delta
- StableLM
- -1 (30d)
- awesome-LLM-resources
- +17 (30d)
Owner type
- StableLM
- Organization
- awesome-LLM-resources
- User
Full report
- StableLM
- Trust report
- awesome-LLM-resources
- Trust report
Choose StableLM if…
- 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.
- More GitHub stars (16k vs 9.0k) - visibility, not fit.
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.
Choose awesome-LLM-resources if…
- Pricing: The repository itself is free to use, but some linked resources may require payment or have associated costs..
- Requirements: The repository does not specify any technical requirements for accessing its content..
- Tags unique to awesome-LLM-resources: awesome-list, book, course, large-language-models.
- Also covers AI Agents, Computer Vision, Data & Retrieval, Developer Tools, Evaluation & Observability, Inference & Serving.
- When you need a comprehensive list of resources for large language models, including multimodal generation, agents, programming assistance, and more.
When NOT to use awesome-LLM-resources
- If you are looking for a tool that provides direct access to LLM APIs or services, as this repository is a list of resources rather than a service provider.
- When you need real-time support or a community forum for troubleshooting LLM-related issues, as this repository is a static list of resources without interactive support.
Explore
StableLM trust report →awesome-LLM-resources trust report →LLM Frameworks category →Model Training category →AI Agents category →Computer Vision category →Data & Retrieval category →Developer Tools category →Evaluation & Observability category →Inference & Serving 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 (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 (WangRongsheng/awesome-LLM-resources) · observed Sep 20, 2026
- GitHub forks (WangRongsheng/awesome-LLM-resources) · observed Sep 20, 2026
- Last push (WangRongsheng/awesome-LLM-resources) · 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 on cards: StableLM 16k · awesome-LLM-resources 9.0k (synced Sep 20, 2026).
Common questions
- What is the difference between StableLM and awesome-LLM-resources?
- StableLM: Stability AI Language Models. awesome-LLM-resources: Summary of the world's best LLM resources.. See the comparison table for live GitHub stats and shared categories.
- When should I choose StableLM over awesome-LLM-resources?
- Choose StableLM over awesome-LLM-resources when 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; More GitHub stars (16k vs 9.0k) - visibility, not fit.
- When should I choose awesome-LLM-resources over StableLM?
- Choose awesome-LLM-resources over StableLM when Pricing: The repository itself is free to use, but some linked resources may require payment or have associated costs.; Requirements: The repository does not specify any technical requirements for accessing its content.; Tags unique to awesome-LLM-resources: awesome-list, book, course, large-language-models; Also covers AI Agents, Computer Vision, Data & Retrieval, Developer Tools, Evaluation & Observability, Inference & Serving; When you need a comprehensive list of resources for large language models, including multimodal generation, agents, programming assistance, and more.
- 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.
- When should I avoid awesome-LLM-resources?
- If you are looking for a tool that provides direct access to LLM APIs or services, as this repository is a list of resources rather than a service provider. When you need real-time support or a community forum for troubleshooting LLM-related issues, as this repository is a static list of resources without interactive support.
- Is StableLM or awesome-LLM-resources more popular on GitHub?
- StableLM has more GitHub stars (15,678 vs 8,968). Stars measure visibility, not whether either tool fits your constraints.
- Are StableLM and awesome-LLM-resources open source?
- Yes - both are open-source projects on GitHub (StableLM: Apache-2.0, awesome-LLM-resources: Apache-2.0).
- Where can I find alternatives to StableLM or awesome-LLM-resources?
- GraphCanon lists graph-backed alternatives at StableLM alternatives and awesome-LLM-resources alternatives (StableLM markdown twin, awesome-LLM-resources 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, StableLM or awesome-LLM-resources?
- StableLM: Dormant. awesome-LLM-resources: Very active. 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 StableLM and awesome-LLM-resources?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: StableLM trust report; awesome-LLM-resources trust report.