Source details
- Original source
- MarkTechPost
- Published
- 2026-06-28
- Primary topic
- Foundation Models
Why it matters
Model launches, benchmark jumps, API upgrades, context window changes, and frontier LLM competition. Use the original source for the full report, then use the directory shortcuts below to compare the products and workflows the story points toward.
What happened
Liquid AI released LFM2.5-230M, its smallest model yet. The 230M-parameter, open-weight model runs on-device at 213 tok/s on a Galaxy S25 Ultra and 42 on a Raspberry Pi 5. Built on the LFM2 architecture, it targets tool use and data extraction, beating larger models like Qwen3.5-0.8B and Gemma 3 1B on instruction following. The post Liquid AI Ships LFM2.5-230M with llama.cpp, MLX, vLLM, SGLang, and ONNX Support for On-Device Inference appeared first on MarkTechPost .
What to do next
Compare the hosted model pages first, then check the related tools and buyer guides before changing workflow standards.
Liquid AI released LFM2.5-230M, its smallest model yet. The 230M-parameter, open-weight model runs on-device at 213 tok/s on a Galaxy S25 Ultra and 42 on a Raspberry Pi 5. Built on the LFM2 architecture, it targets tool use and data extraction, beating larger models like Qwen3.5-0.8B and Gemma 3 1B on instruction following. The post Liquid AI Ships LFM2.5-230M with llama.cpp, MLX, vLLM, SGLang, and ONNX Support for On-Device Inference appeared first on MarkTechPost .
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