Comparison
forge vs llm.ts
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 llm.ts if llm.ts is a TypeScript library for interacting with various Large Language Models via a unified API interface.
Markdown twin · forge alternatives · llm.ts alternatives
GraphCanon updated 4d
Trust & integrity
| Signal | forge | llm.ts |
|---|---|---|
| Maintenance | Very active (0d since push) As of 5d · github_public_v1 | Dormant (1193d since push) As of 4d · github_public_v1 |
| Provenance | Not a fork · Personal account As of 5d · github_public_v1 | Not a fork · Personal account As of 4d · 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
- forge
- A Python framework for self-hosted LLM tool-calling and multi-step agentic workflows
- llm.ts
- Call any LLM with a single API. Zero dependencies.
Stars
- forge
- 2.2k
- llm.ts
- 214
Forks
- forge
- 173
- llm.ts
- 9
Open issues
- forge
- 4
- llm.ts
- 2
Language
- forge
- Python
- llm.ts
- TypeScript
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.
- llm.ts
- llm.ts is a TypeScript library for interacting with various Large Language Models via a unified API interface.
Persona
- forge
- -
- llm.ts
- -
Runtime
- forge
- -
- llm.ts
- -
License
- forge
- MIT
- llm.ts
- MIT License - permissive license that is short and simple, allowing you to use the software in any project as long as this licensing information is retained
Last pushed
- forge
- Aug 13, 2026
- llm.ts
- May 9, 2023
Categories
- forge
- AI Agents, LLM Frameworks
- llm.ts
- LLM Frameworks, Model Training
Trust and health
Maintenance
- forge
- Very active (96%)
- llm.ts
- Dormant (18%)
Days since push
- forge
- 0d
- llm.ts
- 1193d
Open issues (now)
- forge
- 4
- llm.ts
- 2
Stars delta
- forge
- Unknown
- llm.ts
- +1 (30d)
Open issues delta
- forge
- Unknown
- llm.ts
- 0 (30d)
Full report
- forge
- Trust report
- llm.ts
- Trust report
Choose forge if…
- forge is primarily Python; llm.ts is TypeScript.
- 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 llm.ts if…
- llm.ts is primarily TypeScript; forge is Python.
- Supports multiple providers including OpenAI, Cohere, and HuggingFace. Can be extended by opening a PR.
- Tags unique to llm.ts: ai, cohere, huggingface, llm.
- Also covers Model Training.
- You need to interact with multiple LLM providers like OpenAI, Cohere, and HuggingFace through a single API.
When NOT to use llm.ts
- If you require functionalities that are specific to one provider that are not yet unified or supported within the llm.ts framework.
- For projects that aim to minimize dependencies, though llm.ts itself claims zero dependencies, its reliance on external LLM providers could indirectly introduce complexities.
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 Aug 14, 2026
- GitHub forks (antoinezambelli/forge) · observed Aug 14, 2026
- Last push (antoinezambelli/forge) · observed Aug 13, 2026
- License file (MIT) · observed Aug 14, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
- GitHub stars (r2d4/llm.ts) · observed Aug 15, 2026
- GitHub forks (r2d4/llm.ts) · observed Aug 15, 2026
- Last push (r2d4/llm.ts) · observed May 9, 2023
- License file (MIT) · observed Aug 15, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: forge 2.2k · llm.ts 214 (synced Aug 14, 2026).
Common questions
- What is the difference between forge and llm.ts?
- forge: A Python framework for self-hosted LLM tool-calling and multi-step agentic workflows. llm.ts: Call any LLM with a single API. Zero dependencies.. See the comparison table for live GitHub stats and shared categories.
- When should I choose forge over llm.ts?
- Choose forge over llm.ts when forge is primarily Python; llm.ts is TypeScript; 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 llm.ts over forge?
- Choose llm.ts over forge when llm.ts is primarily TypeScript; forge is Python; Supports multiple providers including OpenAI, Cohere, and HuggingFace. Can be extended by opening a PR; Tags unique to llm.ts: ai, cohere, huggingface, llm; Also covers Model Training; You need to interact with multiple LLM providers like OpenAI, Cohere, and HuggingFace through a single API.
- 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 llm.ts?
- If you require functionalities that are specific to one provider that are not yet unified or supported within the llm.ts framework. For projects that aim to minimize dependencies, though llm.ts itself claims zero dependencies, its reliance on external LLM providers could indirectly introduce complexities.
- Is forge or llm.ts more popular on GitHub?
- forge has more GitHub stars (2,217 vs 214). Stars measure visibility, not whether either tool fits your constraints.
- Are forge and llm.ts open source?
- Yes - both are open-source projects on GitHub (forge: MIT, llm.ts: MIT).
- Where can I find alternatives to forge or llm.ts?
- GraphCanon lists graph-backed alternatives at forge alternatives and llm.ts alternatives (forge markdown twin, llm.ts 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 llm.ts?
- forge: Very active. llm.ts: 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 llm.ts?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: forge trust report; llm.ts trust report.