Comparison
forge vs openlm
Verdict
Pick forge if developers working on self-hosted LLM tooling who need flexibility in backend setup and seamless integration of function calling in multi-step workflows might benefit from Forge; pick openlm if openLM is a flexible Python library designed to interface with various Language Model frameworks similarly to the OpenAI API.
Markdown twin · forge alternatives · openlm alternatives
GraphCanon updated Sep 20, 2026
5views this month
Trust & integrity
| Signal | forge | openlm |
|---|---|---|
| Maintenance | Active (19d since push) As of Sep 20, 2026 · github_public_v1 | Dormant (1219d since push) As of Sep 20, 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 20, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 15, 2026 · osv@v1 | Published findings 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
- forge
- A Python framework for self-hosted LLM tool-calling and multi-step agentic workflows
- openlm
- OpenAI-compatible Python client for calling any LLM
Stars
- forge
- 2.2k
- openlm
- 368
Forks
- forge
- 173
- openlm
- 22
Open issues
- forge
- 3
- openlm
- 1
Language
- forge
- Python
- openlm
- Python
Adopt for
- forge
- Developers working on self-hosted LLM tooling who need flexibility in backend setup and seamless integration of function calling in multi-step workflows might benefit from Forge.
- openlm
- OpenLM is a flexible Python library designed to interface with various Language Model frameworks similarly to the OpenAI API.
Persona
- forge
- -
- openlm
- -
Runtime
- forge
- -
- openlm
- -
License
- forge
- MIT
- openlm
- MIT License
Last pushed
- forge
- Sep 1, 2026
- openlm
- May 19, 2023
Categories
- forge
- AI Agents, LLM Frameworks
- openlm
- LLM Frameworks
Trust and health
Maintenance
- forge
- Active (82%)
- openlm
- Dormant (18%)
Days since push
- forge
- 19d
- openlm
- 1219d
Open issues (now)
- forge
- 3
- openlm
- 1
Stars delta
- forge
- +31 (30d)
- openlm
- 0 (30d)
Open issues delta
- forge
- -1 (30d)
- openlm
- 0 (30d)
OSV dependency advisories
- forge
- No lockfile (source not queried)
- openlm
- Published findings
Full report
- forge
- Trust report
- openlm
- Trust report
Shared compatibility
- Python · forge: Python runtime · openlm: Python runtime
Choose forge if…
- Requirements: Min 4 GB RAM; Requires Docker; Requires Python 3.12+ and a running LLM backend.; Can be set up with local backends (e.g., llama.cpp) or Anthropic via its API, requiring an API key for the latter case..
- Tags unique to forge: agentic-ai, function-calling, multi-step-workflows, python-framework.
- Also covers AI Agents.
- forge ships Docker support for self-hosted deployment.
- - You require an agnostic backend setup, such as local LLM backends like llama.cpp or cloud-based services with Anthropic.
When NOT to use forge
- - If your application does not require flexibility in backend selection, and you prefer a single cloud provider like Anthropic without local setup.
- - For scenarios where simplicity of setup outweighs the need for customization in function calling and workflow management.
- - When working within environments strictly regulated against self-hosted infrastructure or requiring fully managed services.
Choose openlm if…
- Requirements: Installation is as simple as using pip to install the openlm package..
- Tags unique to openlm: cohere, huggingface, llm, openai.
- 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (antoinezambelli/forge) · observed Sep 20, 2026
- GitHub forks (antoinezambelli/forge) · observed Sep 20, 2026
- Last push (antoinezambelli/forge) · observed Sep 1, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
- 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 on cards: forge 2.2k · openlm 368 (synced Sep 20, 2026).
Common questions
- What is the difference between forge and openlm?
- forge: A Python framework for self-hosted LLM tool-calling and multi-step agentic workflows. openlm: OpenAI-compatible Python client for calling any LLM. See the comparison table for live GitHub stats and shared categories.
- When should I choose forge over openlm?
- Choose forge over openlm when Requirements: Min 4 GB RAM; Requires Docker; Requires Python 3.12+ and a running LLM backend.; Can be set up with local backends (e.g., llama.cpp) or Anthropic via its API, requiring an API key for the latter case.; Tags unique to forge: agentic-ai, function-calling, multi-step-workflows, python-framework; Also covers AI Agents; forge ships Docker support for self-hosted deployment; - You require an agnostic backend setup, such as local LLM backends like llama.cpp or cloud-based services with Anthropic.
- When should I choose openlm over forge?
- Choose openlm over forge when Requirements: Installation is as simple as using pip to install the openlm package.; Tags unique to openlm: cohere, huggingface, llm, openai; 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 avoid forge?
- - If your application does not require flexibility in backend selection, and you prefer a single cloud provider like Anthropic without local setup. - For scenarios where simplicity of setup outweighs the need for customization in function calling and workflow management. - When working within environments strictly regulated against self-hosted infrastructure or requiring fully managed services.
- 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.
- Is forge or openlm more popular on GitHub?
- forge has more GitHub stars (2,248 vs 368). Stars measure visibility, not whether either tool fits your constraints.
- Are forge and openlm open source?
- Yes - both are open-source projects on GitHub (forge: MIT, openlm: MIT).
- Where can I find alternatives to forge or openlm?
- GraphCanon lists graph-backed alternatives at forge alternatives and openlm alternatives (forge markdown twin, openlm 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, forge or openlm?
- forge: Active. openlm: 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 forge and openlm?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: forge trust report; openlm trust report.