Models & Labs
llama.cpp adds LiquidAI LFM3 model support
llama.cpp Releaseshigh confidence
Why it matters
- →Enables local inference of Liquid AI's novel LFM3 architecture on standard hardware.
- →Adds support for recurrent state rollback, a key differentiator from standard transformers.
- →Expands llama.cpp's model zoo with efficient 1.7B and 2B parameter options.
llama.cpp has added support for Liquid AI's LFM3-1.7B and LFM3-VL-2B models via pull request #31252. The update implements recurrent state rollback, a key feature of the Liquid architecture, enabling efficient inference on various hardware backends including CUDA 12/13, ROCm 10.0, and Apple Silicon with KleidiAI. Specific technical adjustments include keeping LFM3-VL depthwise conv kernels in F32 during quantization and adding Metal fusion baselines for testing. This release expands llama.cpp's compatibility to include Liquid AI's emerging recurrent models.
Read originalThe story around this
Earlier coverage that leads up to this article, and what followed. Lines connect each piece to the closest one after it, converging here.
How we got here
- 1LFM2.5-2.6B: Efficient AI Agents for Local Deployment
Hugging Face Blog · August 4, 2026 · Same story
- 2llama.cpp b10933 Release Expands Platform Support
llama.cpp Releases · September 13, 2026 · Same story
- 3Liquid AI releases DSpark drafter for vision models
Hugging Face Blog · September 24, 2026 · Same story
- 4llama.cpp adds LiquidAI LFM3-Audio and Omni support
llama.cpp Releases · October 28, 2026 · Same story
Follow this story
Open the full story →Liquid AI releases LFM3 multimodal models
3 developments
- Oct 27 · Hugging Face Blog
Liquid AI releases LFM3 multimodal models - Oct 28 · llama.cpp Releases
llama.cpp adds LiquidAI LFM3 model support (This article)↳ llama.cpp adds support for LiquidAI LFM3 models to enable local inference on Apple Silicon and AMD ROCm GPUs. - Oct 30 · llama.cpp Releases
llama.cpp adds OCP FP8 E4M3 support↳ llama.cpp adds OCP FP8 E4M3 quantization support with fast CPU kernels and fixes for fused QKV projections.
More from llama.cpp Releases
Coding Toolscoding
llama.cpp b12022 adds ROCm 10 and Snapdragon support
This release quietly cements llama.cpp as the universal inference runtime by finally bringing ROCm 10.0 to Linux and Windows alongside CUDA 13.4, effectively closing the hardware gap for AMD users who were previously left behind. The inclusion of native Snapdragon support on Linux marks a significant step toward running local LLMs on ARM-based mobile chips without emulation overhead. While KleidiAI on Apple Silicon is disabled in this build, the broader expansion to diverse accelerators ensures that developers aren't locked into NVIDIA ecosystems anymore.
llama.cpp Releases
Coding Toolscoding
llama.cpp b12023 fixes shared prefix bug
This release addresses a specific inference artifact where decision prefixes were incorrectly bleeding into output embeddings. By capping shared prefixes at the first output position, llama.cpp ensures that option tokens remain distinct for parent and child tasks. This is a targeted fix for multi-step reasoning or voting workflows rather than a performance boost. It stabilizes complex generation patterns without changing the underlying model architecture.
llama.cpp Releases
Coding Toolscoding
llama.cpp b12024 adds Snapdragon and ROCm 10
This release quietly expands llama.cpp's hardware support to include Qualcomm Snapdragon devices with CPU, Adreno GPU, and Hexagon NPU acceleration. It also updates ROCm to version 10.0 for both Linux and Windows, keeping AMD users in step with the latest driver stack. CUDA builds now default to 13.4 libraries alongside 12.x options, reflecting the industry's gradual shift toward newer NVIDIA toolkits. While no new model architectures are introduced, the binary matrix grows significantly, ensuring local inference remains viable on a wider array of edge and server hardware.
llama.cpp Releases
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