| Hi r/localllama community, I am happy to announce this week's release of Lemonade v10! The headline feature, Linux support for NPU, was already posted but I wanted to share the big picture as well. Lemonade v9 came out 4 months ago and introduced a new C++ implementation for what was essentially an LLM- and Windows-focused project. Since then, the community has grown a lot and added:
All of this work is in service of making the local AI apps ecosystem more awesome for everyone! The idea is to make it super easy to try models/backends, build multi-modal apps against a single base URL, and make these apps easily portable across a large number of platforms. In terms of what's next, we are partnering with the community to build out more great local-first AI experiences and use cases. We're giving away dozens of high-end Strix Halo 128 GB laptops in the AMD Lemonade Developer Challenge. If you have ideas for the future of NPU and/or multi-modal local AI apps please submit your projects! Thanks as always for this community's support! None of this would be possible without the dozens of contributors and hundreds of y'all providing feedback. If you like what you're doing, please drop us a star on the Lemonade GitHub and come chat about it on Discord! [link] [comments] |
Lemonade v10: Linux NPU support and chock full of multi-modal capabilities
Reddit r/LocalLLaMA / 3/14/2026
📰 NewsDeveloper Stack & InfrastructureTools & Practical Usage
Key Points
- Lemonade v10 adds Linux NPU support, enabling local AI acceleration on compatible hardware and expanding use beyond Windows.
- The release delivers multi-modal capabilities (image generation/editing, transcription, and speech generation) accessible from a single base URL.
- It introduces a control center web and desktop app for managing and testing models and backends, and expands platform support to Ubuntu, Arch, Debian, Fedora, and Snap.
- The team is inviting community participation with the AMD Lemonade Developer Challenge offering hardware prizes to spur future local-first NPU and multi-modal AI use cases.
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