Comparison
openlm vs llm
Verdict
Pick openlm if openLM is a flexible Python library designed to interface with various Language Model frameworks similarly to the OpenAI API; pick llm if decision-critical facts for 'llm'.
Markdown twin · openlm alternatives · llm alternatives
GraphCanon updated Sep 20, 2026
7views this month
Trust & integrity
| Signal | openlm | llm |
|---|---|---|
| Maintenance | Dormant (1219d since push) As of Sep 20, 2026 · github_public_v1 | Very active (4d since push) As of Sep 7, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 20, 2026 · github_public_v1 | Not a fork · Personal account As of Sep 7, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings 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 |
Tagline
- openlm
- OpenAI-compatible Python client for calling any LLM
- llm
- Access large language models from the command-line
Stars
- openlm
- 368
- llm
- 12k
Forks
- openlm
- 22
- llm
- 978
Open issues
- openlm
- 1
- llm
- 689
Language
- openlm
- Python
- llm
- Python
Adopt for
- openlm
- OpenLM is a flexible Python library designed to interface with various Language Model frameworks similarly to the OpenAI API.
- llm
- Decision-critical facts for 'llm'
Persona
- openlm
- -
- llm
- -
Runtime
- openlm
- -
- llm
- -
License
- openlm
- MIT License
- llm
- Apache-2.0
Last pushed
- openlm
- May 19, 2023
- llm
- Sep 2, 2026
Categories
- openlm
- LLM Frameworks
- llm
- Inference & Serving, LLM Frameworks
Trust and health
Maintenance
- openlm
- Dormant (18%)
- llm
- Very active (96%)
Days since push
- openlm
- 1219d
- llm
- 4d
Open issues (now)
- openlm
- 1
- llm
- 689
Stars delta
- openlm
- 0 (30d)
- llm
- +149 (30d)
Open issues delta
- openlm
- 0 (30d)
- llm
- +25 (30d)
OSV dependency advisories
- openlm
- Published findings
- llm
- No lockfile (source not queried)
Full report
- openlm
- Trust report
- llm
- Trust report
Shared compatibility
- Python · openlm: Python runtime · llm: Python runtime
Choose openlm if…
- License: openlm is MIT, llm is Apache-2.0.
- Requirements: Installation is as simple as using pip to install the openlm package..
- Tags unique to openlm: cohere, huggingface, llm.
- Use when you want to seamlessly integrate different LLM frameworks, like Hugging Face or Cohere, under a uniform interface similar to OpenAI’s.
When NOT to use openlm
- Avoid when you require maximum performance optimization specific to one LLM framework, as using an intermediary library like OpenLM might introduce additional overhead.
- Not suitable if you are strictly working with models that do not have Python support or don't fit within the frameworks supported by OpenLM.
Choose llm if…
- License: llm is Apache-2.0, openlm 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.
- Also covers Inference & Serving.
- - 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 (r2d4/openlm) · observed Sep 20, 2026
- GitHub forks (r2d4/openlm) · observed Sep 20, 2026
- Last push (r2d4/openlm) · observed May 19, 2023
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (simonw/llm) · observed Sep 20, 2026
- GitHub forks (simonw/llm) · observed Sep 20, 2026
- Last push (simonw/llm) · observed Sep 2, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: openlm 368 · llm 12k (synced Sep 20, 2026).
Common questions
- What is the difference between openlm and llm?
- openlm: OpenAI-compatible Python client for calling any LLM. llm: Access large language models from the command-line. See the comparison table for live GitHub stats and shared categories.
- When should I choose openlm over llm?
- Choose openlm over llm when License: openlm is MIT, llm is Apache-2.0; Requirements: Installation is as simple as using pip to install the openlm package.; Tags unique to openlm: cohere, huggingface, llm; Use when you want to seamlessly integrate different LLM frameworks, like Hugging Face or Cohere, under a uniform interface similar to OpenAI’s.
- When should I choose llm over openlm?
- Choose llm over openlm when License: llm is Apache-2.0, openlm 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; Also covers Inference & Serving; - 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 openlm?
- Avoid when you require maximum performance optimization specific to one LLM framework, as using an intermediary library like OpenLM might introduce additional overhead. Not suitable if you are strictly working with models that do not have Python support or don't fit within the frameworks supported by OpenLM.
- 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 openlm or llm more popular on GitHub?
- llm has more GitHub stars (12,473 vs 368). Stars measure visibility, not whether either tool fits your constraints.
- Are openlm and llm open source?
- Yes - both are open-source projects on GitHub (openlm: MIT, llm: Apache-2.0).
- Where can I find alternatives to openlm or llm?
- GraphCanon lists graph-backed alternatives at openlm alternatives and llm alternatives (openlm 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, openlm or llm?
- openlm: Dormant. 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 openlm and llm?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: openlm trust report; llm trust report.