--- title: "OpenLLM vs LocalAI" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/bentoml-openllm-vs-mudler-localai" tools: ["bentoml-openllm", "mudler-localai"] --- # OpenLLM vs LocalAI *GraphCanon updated Sep 20, 2026* ## Verdict Pick OpenLLM if use OpenLLM for easy deployment of a wide range of open-source LLMs through an OpenAI-compatible API with support for cloud environments and fine-tuning; pick LocalAI if localAI is an open-source AI engine that supports running a variety of models including LLMs, vision, voice, image, and video models on any hardware without requiring a GPU. [OpenLLM](https://bentoml.com) reports 13k GitHub stars, 837 forks, and 17 open issues, last pushed Aug 31, 2026. [LocalAI](https://localai.io) has 49k stars, 4.5k forks, and 178 open issues, last pushed Sep 18, 2026. Figures are from public GitHub metadata via [OpenLLM's repository](https://github.com/bentoml/OpenLLM) and [LocalAI's repository](https://github.com/mudler/LocalAI). | | [OpenLLM](/tools/bentoml-openllm.md) | [LocalAI](/tools/mudler-localai.md) | | --- | --- | --- | | Tagline | Run any open-source LLMs as OpenAI compatible API endpoint in the cloud. | Open-source AI engine for running various models on any hardware | | Stars | 12,527 | 49,150 | | Forks | 837 | 4,457 | | Open issues | 17 | 178 | | Language | Python | Go | | Adopt for | Use OpenLLM for easy deployment of a wide range of open-source LLMs through an OpenAI-compatible API with support for cloud environments and fine-tuning. | LocalAI is an open-source AI engine that supports running a variety of models including LLMs, vision, voice, image, and video models on any hardware without requiring a GPU. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | Inference & Serving, Model Training | AI Agents, Computer Vision, Data & Retrieval, Inference & Serving, LLM Frameworks, Model Training, Speech & Audio | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [OpenLLM](/tools/bentoml-openllm.md) | [LocalAI](/tools/mudler-localai.md) | | --- | --- | --- | | Days since push | 6d | 0d | | Open issues (now) | 17 | 178 | | Stars delta | +73 (30d) | +650 (30d) | | Open issues delta | -1 (30d) | +22 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/bentoml-openllm/trust.md) | [trust report](/tools/mudler-localai/trust.md) | ## Decision facts: OpenLLM - **Adopt for:** Use OpenLLM for easy deployment of a wide range of open-source LLMs through an OpenAI-compatible API with support for cloud environments and fine-tuning. ## Decision facts: LocalAI - **Adopt for:** LocalAI is an open-source AI engine that supports running a variety of models including LLMs, vision, voice, image, and video models on any hardware without requiring a GPU. ## Choose when ### Choose OpenLLM if… - OpenLLM is primarily Python; LocalAI is Go. - License: OpenLLM is Apache-2.0, LocalAI is MIT. - Tags unique to OpenLLM: bentoml, fine-tuning, llama, llm-inference. - You require OpenAI-compatible APIs to serve a diverse set of state-of-the-art open-source LLMs, such as DeepSeek, Llama, or Qwen2.5, in both local and cloud deployment scenarios. ### Choose LocalAI if… - LocalAI is primarily Go; OpenLLM is Python. - License: LocalAI is MIT, OpenLLM is Apache-2.0. - Tags unique to LocalAI: agents, ai, api, audio-generation. - Also covers AI Agents, Computer Vision, Data & Retrieval, LLM Frameworks, Speech & Audio. - LocalAI ships Docker support for self-hosted deployment. - When you need to run AI models on hardware that lacks a GPU, as LocalAI supports CPU-only operations. ## When NOT to use OpenLLM - If your project primarily focuses on proprietary models that are not open-source and you do not want to convert or migrate them to an OpenAI-compatible API. - In situations where direct model weight management is required for compliance or security reasons, as OpenLLM does not store the model weights. ## When NOT to use LocalAI - If your project specifically requires GPU acceleration for performance reasons, as LocalAI can run on CPU-only setups but may not offer the same speed as GPU-accelerated alternatives. - When you need a tool that is tightly integrated with specific cloud services or proprietary hardware, as LocalAI is designed for flexibility across different hardware types. - If your project demands a proprietary solution with commercial support, as LocalAI is an open-source project with community-driven support. ## Common questions ### What is the difference between OpenLLM and LocalAI? OpenLLM: Run any open-source LLMs as OpenAI compatible API endpoint in the cloud.. LocalAI: Open-source AI engine for running various models on any hardware. See the comparison table for live GitHub stats and shared categories. ### When should I choose OpenLLM over LocalAI? Choose OpenLLM over LocalAI when OpenLLM is primarily Python; LocalAI is Go; License: OpenLLM is Apache-2.0, LocalAI is MIT; Tags unique to OpenLLM: bentoml, fine-tuning, llama, llm-inference; You require OpenAI-compatible APIs to serve a diverse set of state-of-the-art open-source LLMs, such as DeepSeek, Llama, or Qwen2.5, in both local and cloud deployment scenarios. ### When should I choose LocalAI over OpenLLM? Choose LocalAI over OpenLLM when LocalAI is primarily Go; OpenLLM is Python; License: LocalAI is MIT, OpenLLM is Apache-2.0; Tags unique to LocalAI: agents, ai, api, audio-generation; Also covers AI Agents, Computer Vision, Data & Retrieval, LLM Frameworks, Speech & Audio; LocalAI ships Docker support for self-hosted deployment; When you need to run AI models on hardware that lacks a GPU, as LocalAI supports CPU-only operations. ### When should I avoid OpenLLM? If your project primarily focuses on proprietary models that are not open-source and you do not want to convert or migrate them to an OpenAI-compatible API. In situations where direct model weight management is required for compliance or security reasons, as OpenLLM does not store the model weights. ### When should I avoid LocalAI? If your project specifically requires GPU acceleration for performance reasons, as LocalAI can run on CPU-only setups but may not offer the same speed as GPU-accelerated alternatives. When you need a tool that is tightly integrated with specific cloud services or proprietary hardware, as LocalAI is designed for flexibility across different hardware types. If your project demands a proprietary solution with commercial support, as LocalAI is an open-source project with community-driven support. ### Is OpenLLM or LocalAI more popular on GitHub? LocalAI has more GitHub stars (49,150 vs 12,527). Stars measure visibility, not whether either tool fits your constraints. ### Are OpenLLM and LocalAI open source? Yes - both are open-source projects on GitHub (OpenLLM: Apache-2.0, LocalAI: MIT). ### Where can I find alternatives to OpenLLM or LocalAI? GraphCanon lists graph-backed alternatives at [OpenLLM alternatives](/tools/bentoml-openllm/alternatives) and [LocalAI alternatives](/tools/mudler-localai/alternatives) ([OpenLLM markdown twin](/tools/bentoml-openllm/alternatives.md), [LocalAI markdown twin](/tools/mudler-localai/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/bentoml-openllm-vs-mudler-localai.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, OpenLLM or LocalAI? OpenLLM: Very active. LocalAI: 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 OpenLLM and LocalAI? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [OpenLLM trust report](/tools/bentoml-openllm/trust); [LocalAI trust report](/tools/mudler-localai/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=bentoml-openllm`](/api/graphcanon/graph?tool=bentoml-openllm) - 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/_