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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 Sep 20, 2026

7views this month

guidance logo

guidance

guidance-ai/guidance

★ 22kpushed May 21, 2026
vs
llm logo

llm

simonw/llm

★ 12kpushed Sep 2, 2026

Trust & integrity

Signalguidancellm
Maintenance
Slowing (108d since push)
As of Sep 7, 2026 · github_public_v1
Very active (4d since push)
As of Sep 7, 2026 · github_public_v1
Provenance
Not a fork · Organization account
As of Sep 7, 2026 · github_public_v1
Not a fork · Personal account
As of Sep 7, 2026 · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of Jul 11, 2026 · osv@v1
No lockfile (source not queried)
As of Jul 11, 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
guidance trust reportllm trust reportTrust methodology

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
978

Open issues

guidance
323
llm
689

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
Sep 2, 2026

Categories

guidance
Inference & Serving, LLM Frameworks
llm
Inference & Serving, LLM Frameworks

Trust and health

Maintenance

guidance
Slowing (36%)
llm
Very active (96%)

Days since push

guidance
108d
llm
4d

Open issues (now)

guidance
323
llm
689

Stars delta

guidance
+33 (30d)
llm
+149 (30d)

Open issues delta

guidance
+7 (30d)
llm
+25 (30d)

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
GitHubDetails

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.
GitHubDetails

Explore

guidance trust report →llm trust report →Inference & Serving category →LLM Frameworks 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 on cards: guidance 22k · llm 12k (synced Sep 20, 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, 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 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 (21,739 vs 12,473). 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: Slowing. 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.

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