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Comparison

rig vs forge

Verdict

Pick rig if rig is a Rust library designed to create modular and scalable LLM applications with extensive support for agentic workflows, multi-turn streaming, full compatibility with GenAI conventions, and integration capabilities; 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.

Markdown twin · rig alternatives · forge alternatives

GraphCanon updated Sep 30, 2026

rig logo

rig

0xPlaygrounds/rig

★ 8.7kpushed Sep 19, 2026
vs
forge logo

forge

antoinezambelli/forge

★ 2.2kpushed Sep 1, 2026

Trust & integrity

Signalrigforge
Maintenance
Very active (0d since push)
As of Sep 20, 2026 · github_public_v1
Active (19d since push)
As of Sep 20, 2026 · github_public_v1
Provenance
Not a fork · Organization 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 11, 2026 · osv@v1
No lockfile (source not queried)
As of Jul 15, 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
rig trust reportforge trust reportTrust methodology

Tagline

rig
Build modular and scalable LLM Applications in Rust
forge
A Python framework for self-hosted LLM tool-calling and multi-step agentic workflows

Stars

rig
8.7k
forge
2.2k

Forks

rig
974
forge
173

Open issues

rig
102
forge
3

Language

rig
Rust
forge
Python

Adopt for

rig
Rig is a Rust library designed to create modular and scalable LLM applications with extensive support for agentic workflows, multi-turn streaming, full compatibility with GenAI conventions, and integration capabilities.
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.

Persona

rig
-
forge
-

Runtime

rig
-
forge
-

License

rig
MIT
forge
MIT

Last pushed

rig
Sep 19, 2026
forge
Sep 1, 2026

Categories

rig
AI Agents, LLM Frameworks
forge
AI Agents, LLM Frameworks

Trust and health

Maintenance

rig
Very active (96%)
forge
Active (82%)

Days since push

rig
0d
forge
19d

Open issues (now)

rig
102
forge
3

Stars delta

rig
+351 (30d)
forge
+31 (30d)

Open issues delta

rig
-11 (30d)
forge
-1 (30d)

Owner type

rig
Organization
forge
User

Full report

rig
Trust report
forge
Trust report

Choose rig if…

  • rig is primarily Rust; forge is Python.
  • Self-hosted as a Rust library.
  • Pricing: Free to use under MIT license with potential premium support options..
  • Tags unique to rig: agent, ai, artificial-intelligence, automation.
  • You should use Rig when you need to work with LLM applications in Rust and want full WASM (core library) compatibility.

When NOT to use rig

  • Avoid using Rig if you are working on applications that do not require or support Rust as it is specifically built to facilitate LLM operations within a Rust environment.
  • Rig may not be suitable if your project cannot handle potential breaking changes, which are expected due to its rapidly evolving nature and upcoming feature updates.
GitHubDetails

Choose forge if…

  • forge is primarily Python; rig is Rust.
  • 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.
  • 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.
GitHubDetails

Explore

rig trust report →forge trust report →AI Agents 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: rig 8.7k · forge 2.2k (synced Sep 20, 2026).

Common questions

What is the difference between rig and forge?
rig: Build modular and scalable LLM Applications in Rust. forge: A Python framework for self-hosted LLM tool-calling and multi-step agentic workflows. See the comparison table for live GitHub stats and shared categories.
When should I choose rig over forge?
Choose rig over forge when rig is primarily Rust; forge is Python; Self-hosted as a Rust library; Pricing: Free to use under MIT license with potential premium support options.; Tags unique to rig: agent, ai, artificial-intelligence, automation; You should use Rig when you need to work with LLM applications in Rust and want full WASM (core library) compatibility.
When should I choose forge over rig?
Choose forge over rig when forge is primarily Python; rig is Rust; 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; 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 avoid rig?
Avoid using Rig if you are working on applications that do not require or support Rust as it is specifically built to facilitate LLM operations within a Rust environment. Rig may not be suitable if your project cannot handle potential breaking changes, which are expected due to its rapidly evolving nature and upcoming feature updates.
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.
Is rig or forge more popular on GitHub?
rig has more GitHub stars (8,679 vs 2,248). Stars measure visibility, not whether either tool fits your constraints.
Are rig and forge open source?
Yes - both are open-source projects on GitHub (rig: MIT, forge: MIT).
Where can I find alternatives to rig or forge?
GraphCanon lists graph-backed alternatives at rig alternatives and forge alternatives (rig markdown twin, forge 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, rig or forge?
rig: Very active. forge: 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 rig and forge?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: rig trust report; forge trust report.

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