--- title: "Foundry-Local vs afm-Server" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/microsoft-foundry-local-vs-techopolis-afm-server" tools: ["microsoft-foundry-local", "techopolis-afm-server"] --- # Foundry-Local vs afm-Server *GraphCanon updated Aug 13, 2026* ## Verdict Pick Foundry-Local if foundry-Local offers SDK and CLI for local GPU-accelerated AI inference, focusing on speech-to-text models such as Whisper, using ONNX Runtime; pick afm-Server if afm-Server provides macOS users with local access to Apple's on-device foundational AI models through an API compatible with OpenAI standards. [Foundry-Local](https://foundrylocal.ai) reports 2.5k GitHub stars, 348 forks, and 71 open issues, last pushed Jul 30, 2026. [afm-Server](https://github.com/Techopolis-Online/Perspective-Intelligence) has 189 stars, 8 forks, and 1 open issues, last pushed Jun 2, 2026. Figures are from public GitHub metadata via [Foundry-Local's repository](https://github.com/microsoft/Foundry-Local) and [afm-Server's repository](https://github.com/Techopolis/afm-Server). | | [Foundry-Local](/tools/microsoft-foundry-local.md) | [afm-Server](/tools/techopolis-afm-server.md) | | --- | --- | --- | | Tagline | SDK and CLI for local AI inference with GPU acceleration, supporting speech-to-text models like Whisper. | macOS menu bar app for exposing Apple's on-device Foundation Models via an OpenAI-compatible API | | Stars | 2,479 | 189 | | Forks | 348 | 8 | | Open issues | 71 | 1 | | Language | C++ | Swift | | Adopt for | Foundry-Local offers SDK and CLI for local GPU-accelerated AI inference, focusing on speech-to-text models such as Whisper, using ONNX Runtime. | afm-Server provides macOS users with local access to Apple's on-device foundational AI models through an API compatible with OpenAI standards. | | Persona | - | - | | Runtime | - | - | | License | SDK is licensed under the MIT License. The CLI uses the Microsoft Software License Terms. Models available with Foundry-Local are individually licensed as per their documentation or download page. | MIT | | Categories | Inference & Serving, Speech & Audio | Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Foundry-Local](/tools/microsoft-foundry-local.md) | [afm-Server](/tools/techopolis-afm-server.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Steady (60%) | | Days since push | 0d | 72d | | Open issues (now) | 71 | 1 | | Full report | [trust report](/tools/microsoft-foundry-local/trust.md) | [trust report](/tools/techopolis-afm-server/trust.md) | ## Decision facts: Foundry-Local - **Pricing:** freemium - Free to use SDK and CLI under MIT and Microsoft licenses, individual AI models subject to their own license terms. - **Adopt for:** Foundry-Local offers SDK and CLI for local GPU-accelerated AI inference, focusing on speech-to-text models such as Whisper, using ONNX Runtime. - **License detail:** SDK is licensed under the MIT License. The CLI uses the Microsoft Software License Terms. Models available with Foundry-Local are individually licensed as per their documentation or download page. ## Decision facts: afm-Server - **Adopt for:** afm-Server provides macOS users with local access to Apple's on-device foundational AI models through an API compatible with OpenAI standards. ## Choose when ### Choose Foundry-Local if… - Foundry-Local is primarily C++; afm-Server is Swift. - License: Foundry-Local is Other, afm-Server is MIT. - Pricing: Free to use SDK and CLI under MIT and Microsoft licenses, individual AI models subject to their own license terms.. - Tags unique to Foundry-Local: ai-sdk, chat-completions, foundry-local, gpu acceleration. - Also covers Speech & Audio. - Need to run AI models locally with GPU acceleration ### Choose afm-Server if… - afm-Server is primarily Swift; Foundry-Local is C++. - License: afm-Server is MIT, Foundry-Local is Other. - Tags unique to afm-Server: apple-intelligence, foundation-models, local-llm, macos. - When you need local, cloud-free inference services from Apple's device-based AI models and are working within a macOS environment ## When NOT to use Foundry-Local - Require cloud-based inference services for resource-intensive tasks - Prefer using models not supported by ONNX Runtime or Whisper ## When NOT to use afm-Server - In scenarios where a cross-platform solution is necessary as afm-Server only supports macOS environments - When your application demands real-time, high-throughput API access that can be limited by the device's hardware capabilities compared to cloud solutions ## Common questions ### What is the difference between Foundry-Local and afm-Server? Foundry-Local: SDK and CLI for local AI inference with GPU acceleration, supporting speech-to-text models like Whisper.. afm-Server: macOS menu bar app for exposing Apple's on-device Foundation Models via an OpenAI-compatible API. See the comparison table for live GitHub stats and shared categories. ### When should I choose Foundry-Local over afm-Server? Choose Foundry-Local over afm-Server when Foundry-Local is primarily C++; afm-Server is Swift; License: Foundry-Local is Other, afm-Server is MIT; Pricing: Free to use SDK and CLI under MIT and Microsoft licenses, individual AI models subject to their own license terms.; Tags unique to Foundry-Local: ai-sdk, chat-completions, foundry-local, gpu acceleration; Also covers Speech & Audio; Need to run AI models locally with GPU acceleration. ### When should I choose afm-Server over Foundry-Local? Choose afm-Server over Foundry-Local when afm-Server is primarily Swift; Foundry-Local is C++; License: afm-Server is MIT, Foundry-Local is Other; Tags unique to afm-Server: apple-intelligence, foundation-models, local-llm, macos; When you need local, cloud-free inference services from Apple's device-based AI models and are working within a macOS environment. ### When should I avoid Foundry-Local? Require cloud-based inference services for resource-intensive tasks Prefer using models not supported by ONNX Runtime or Whisper ### When should I avoid afm-Server? In scenarios where a cross-platform solution is necessary as afm-Server only supports macOS environments When your application demands real-time, high-throughput API access that can be limited by the device's hardware capabilities compared to cloud solutions ### Is Foundry-Local or afm-Server more popular on GitHub? Foundry-Local has more GitHub stars (2,479 vs 189). Stars measure visibility, not whether either tool fits your constraints. ### Are Foundry-Local and afm-Server open source? Yes - both are open-source projects on GitHub (Foundry-Local: Other, afm-Server: MIT). ### Where can I find alternatives to Foundry-Local or afm-Server? GraphCanon lists graph-backed alternatives at [Foundry-Local alternatives](/tools/microsoft-foundry-local/alternatives) and [afm-Server alternatives](/tools/techopolis-afm-server/alternatives) ([Foundry-Local markdown twin](/tools/microsoft-foundry-local/alternatives.md), [afm-Server markdown twin](/tools/techopolis-afm-server/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/microsoft-foundry-local-vs-techopolis-afm-server.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Foundry-Local or afm-Server? Foundry-Local: Very active. afm-Server: Steady. 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 Foundry-Local and afm-Server? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Foundry-Local trust report](/tools/microsoft-foundry-local/trust); [afm-Server trust report](/tools/techopolis-afm-server/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=microsoft-foundry-local`](/api/graphcanon/graph?tool=microsoft-foundry-local) - 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/_