--- title: "forge vs OmAgent" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/antoinezambelli-forge-vs-om-ai-lab-omagent" tools: ["antoinezambelli-forge", "om-ai-lab-omagent"] --- # forge vs OmAgent *GraphCanon updated Sep 20, 2026* ## 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 OmAgent if omAgent is a Python library for developing multimodal language agents that supports GPT, Gemini, LLaMA, and LLAVA models. [forge](https://github.com/antoinezambelli/forge) reports 2.2k GitHub stars, 173 forks, and 3 open issues, last pushed Sep 1, 2026. [OmAgent](https://om-agent.com) has 2.7k stars, 292 forks, and 21 open issues, last pushed Mar 19, 2025. Figures are from public GitHub metadata via [forge's repository](https://github.com/antoinezambelli/forge) and [OmAgent's repository](https://github.com/om-ai-lab/OmAgent). | | [forge](/tools/antoinezambelli-forge.md) | [OmAgent](/tools/om-ai-lab-omagent.md) | | --- | --- | --- | | Tagline | A Python framework for self-hosted LLM tool-calling and multi-step agentic workflows | Build multimodal language agents for fast prototype and production | | Stars | 2,248 | 2,667 | | Forks | 173 | 292 | | Open issues | 3 | 21 | | Language | Python | Python | | Adopt for | 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. | OmAgent is a Python library for developing multimodal language agents that supports GPT, Gemini, LLaMA, and LLAVA models. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | AI Agents, LLM Frameworks | AI Agents, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [forge](/tools/antoinezambelli-forge.md) | [OmAgent](/tools/om-ai-lab-omagent.md) | | --- | --- | --- | | Maintenance | Active (82%) | Dormant (18%) | | Days since push | 19d | 545d | | Open issues (now) | 3 | 21 | | Stars delta | +31 (30d) | +2 (30d) | | Open issues delta | -1 (30d) | 0 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/antoinezambelli-forge/trust.md) | [trust report](/tools/om-ai-lab-omagent/trust.md) | ## Shared compatibility - **Python**: [forge](/tools/antoinezambelli-forge.md) - Python runtime; [OmAgent](/tools/om-ai-lab-omagent.md) - Python runtime ## Decision facts: forge - **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. - **Adopt for:** 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. ## Decision facts: OmAgent - **Requirements:** Requires Python >= 3.10 - **Adopt for:** OmAgent is a Python library for developing multimodal language agents that supports GPT, Gemini, LLaMA, and LLAVA models. ## Choose when ### Choose forge if… - License: forge is MIT, OmAgent is Apache-2.0. - 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. ### Choose OmAgent if… - License: OmAgent is Apache-2.0, forge is MIT. - Requirements: Requires Python >= 3.10. - Tags unique to OmAgent: agent, chatbot, gemini, gpt. - Use OmAgent if you are prototyping scenarios involving smart hardware and multimodal workflows. ## 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. ## When NOT to use OmAgent - Avoid using OmAgent if your project does not require support for multimodal models or specific integrations with GPT, Gemini, LLaMA, and LLAVA. - If a lightweight solution is required and advanced multimodal features are unnecessary, another tool might be more suited. ## Common questions ### What is the difference between forge and OmAgent? forge: A Python framework for self-hosted LLM tool-calling and multi-step agentic workflows. OmAgent: Build multimodal language agents for fast prototype and production. See the comparison table for live GitHub stats and shared categories. ### When should I choose forge over OmAgent? Choose forge over OmAgent when License: forge is MIT, OmAgent is Apache-2.0; 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 choose OmAgent over forge? Choose OmAgent over forge when License: OmAgent is Apache-2.0, forge is MIT; Requirements: Requires Python >= 3.10; Tags unique to OmAgent: agent, chatbot, gemini, gpt; Use OmAgent if you are prototyping scenarios involving smart hardware and multimodal workflows. ### 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 OmAgent? Avoid using OmAgent if your project does not require support for multimodal models or specific integrations with GPT, Gemini, LLaMA, and LLAVA. If a lightweight solution is required and advanced multimodal features are unnecessary, another tool might be more suited. ### Is forge or OmAgent more popular on GitHub? OmAgent has more GitHub stars (2,667 vs 2,248). Stars measure visibility, not whether either tool fits your constraints. ### Are forge and OmAgent open source? Yes - both are open-source projects on GitHub (forge: MIT, OmAgent: Apache-2.0). ### Where can I find alternatives to forge or OmAgent? GraphCanon lists graph-backed alternatives at [forge alternatives](/tools/antoinezambelli-forge/alternatives) and [OmAgent alternatives](/tools/om-ai-lab-omagent/alternatives) ([forge markdown twin](/tools/antoinezambelli-forge/alternatives.md), [OmAgent markdown twin](/tools/om-ai-lab-omagent/alternatives.md)), 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](/compare/antoinezambelli-forge-vs-om-ai-lab-omagent.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, forge or OmAgent? forge: Active. OmAgent: 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 OmAgent? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [forge trust report](/tools/antoinezambelli-forge/trust); [OmAgent trust report](/tools/om-ai-lab-omagent/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=antoinezambelli-forge`](/api/graphcanon/graph?tool=antoinezambelli-forge) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_