Comparison
guidance vs llm
Verdict
Pick guidance if guidance is a specialized tool written in Jupyter Notebooks that provides a unique language to control large language models (LLMs) across multiple backends such as Transformers, llama.cpp, and OpenAI. It's open-source,轻; pick llm if decision-critical facts for 'llm'.
Markdown twin · guidance alternatives · llm alternatives
GraphCanon updated 1w
Trust & integrity
| Signal | guidance | llm |
|---|---|---|
| Maintenance | Steady (78d since push) As of 1w · github_public_v1 | Very active (2d since push) As of 1w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 1w · github_public_v1 | Not a fork · Personal account As of 1w · 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
- guidance
- A guidance language for controlling large language models.
- llm
- Access large language models from the command-line
Stars
- guidance
- 22k
- llm
- 12k
Forks
- guidance
- 1.2k
- llm
- 939
Open issues
- guidance
- 316
- llm
- 664
Language
- guidance
- Jupyter Notebook
- llm
- Python
Adopt for
- guidance
- Guidance is a specialized tool written in Jupyter Notebooks that provides a unique language to control large language models (LLMs) across multiple backends such as Transformers, llama.cpp, and OpenAI. It's open-source,轻
- llm
- Decision-critical facts for 'llm'
Persona
- guidance
- -
- llm
- -
Runtime
- guidance
- -
- llm
- -
License
- guidance
- MIT
- llm
- Apache-2.0
Last pushed
- guidance
- May 21, 2026
- llm
- Aug 5, 2026
Categories
- guidance
- Inference & Serving, LLM Frameworks
- llm
- Inference & Serving, LLM Frameworks
Trust and health
Maintenance
- guidance
- Steady (60%)
- llm
- Very active (96%)
Days since push
- guidance
- 78d
- llm
- 2d
Open issues (now)
- guidance
- 316
- llm
- 664
Owner type
- guidance
- Organization
- llm
- User
Full report
- guidance
- Trust report
- llm
- Trust report
Shared compatibility
- Python · guidance: Python runtime · llm: Python runtime
Choose guidance if…
- guidance is primarily Jupyter Notebook; llm is Python.
- License: guidance is MIT, llm is Apache-2.0.
- Tags unique to guidance: backend support, control language, language-models, pip-installable.
- When you need a specific language to finely control various LLM backends including Transformers, llama.cpp, and OpenAI
When NOT to use guidance
- When your project is strictly confined to using only one type of backend which you can manage without a specialized control language
- If your development environment does not support or prefer Jupyter Notebooks, Guidance may not be the best choice
Choose llm if…
- llm is primarily Python; guidance is Jupyter Notebook.
- License: llm is Apache-2.0, guidance is MIT.
- Requirements: - Installation supports multiple methods including `pip`, Homebrew (with caveats noted), `pipx`, and `uv`.; - Requires an OpenAI API key for certain functionalities..
- Tags unique to llm: ai, llms, openai.
- - You prioritize command-line interaction over graphical interfaces, as llm is designed to provide a seamless CLI experience with multiple installation methods.
When NOT to use llm
- - If you require real-time visual feedback or a graphical interface for interacting with language models, as llm is strictly command-line-based.
- - If your primary focus is on model training rather than inference or serving, since llm is aimed at accessing and using pre-trained models.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (guidance-ai/guidance) · observed Aug 7, 2026
- GitHub forks (guidance-ai/guidance) · observed Aug 7, 2026
- Last push (guidance-ai/guidance) · observed May 21, 2026
- License file (MIT) · observed Aug 7, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (simonw/llm) · observed Aug 8, 2026
- GitHub forks (simonw/llm) · observed Aug 8, 2026
- Last push (simonw/llm) · observed Aug 5, 2026
- License file (Apache-2.0) · observed Aug 8, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: guidance 22k · llm 12k (synced Aug 7, 2026).
Common questions
- What is the difference between guidance and llm?
- guidance: A guidance language for controlling large language models.. llm: Access large language models from the command-line. See the comparison table for live GitHub stats and shared categories.
- When should I choose guidance over llm?
- Choose guidance over llm when guidance is primarily Jupyter Notebook; llm is Python; License: guidance is MIT, llm is Apache-2.0; Tags unique to guidance: backend support, control language, language-models, pip-installable; When you need a specific language to finely control various LLM backends including Transformers, llama.cpp, and OpenAI.
- When should I choose llm over guidance?
- Choose llm over guidance when llm is primarily Python; guidance is Jupyter Notebook; License: llm is Apache-2.0, guidance is MIT; Requirements: - Installation supports multiple methods including
pip, Homebrew (with caveats noted),pipx, anduv.; - Requires an OpenAI API key for certain functionalities.; Tags unique to llm: ai, llms, openai; - You prioritize command-line interaction over graphical interfaces, as llm is designed to provide a seamless CLI experience with multiple installation methods. - When should I avoid guidance?
- When your project is strictly confined to using only one type of backend which you can manage without a specialized control language If your development environment does not support or prefer Jupyter Notebooks, Guidance may not be the best choice
- When should I avoid llm?
- - If you require real-time visual feedback or a graphical interface for interacting with language models, as llm is strictly command-line-based. - If your primary focus is on model training rather than inference or serving, since llm is aimed at accessing and using pre-trained models.
- Is guidance or llm more popular on GitHub?
- guidance has more GitHub stars (21,706 vs 12,324). Stars measure visibility, not whether either tool fits your constraints.
- Are guidance and llm open source?
- Yes - both are open-source projects on GitHub (guidance: MIT, llm: Apache-2.0).
- Where can I find alternatives to guidance or llm?
- GraphCanon lists graph-backed alternatives at guidance alternatives and llm alternatives (guidance markdown twin, 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, guidance or llm?
- guidance: Steady. llm: 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 guidance and llm?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: guidance trust report; llm trust report.