Models & Labs
llama.cpp adds LiquidAI LFM3-Audio and Omni support
llama.cpp Releaseshigh confidence
Why it matters
- →LiquidAI's LFM3 models now run locally with high-fidelity audio output.
- →Encoder convolutions are preserved during quantization to prevent audio degradation.
- →Built-in TTS support allows for immediate voice synthesis without external tools.
llama.cpp has released an update adding support for LiquidAI's LFM3-Audio-2B and LFM3-Omni-2B models. The release includes specific conversion logic to handle the unique configuration layout of these transformers, ensuring encoder convolutions remain unquantized to preserve audio quality. It also adds text-to-speech capabilities with selectable male and female voices via the CLI and server interfaces. Binaries are available for macOS, Linux, Windows, and Android across CPU, CUDA, ROCm, and Vulkan backends.
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
- 1Ollama adds local TTS with Phonon and MLX acceleration
Ollama Blog · October 24, 2026 · Related
- 2llama.cpp adds Soprano TTS support
llama.cpp Releases · October 24, 2026 · Same story
- 3Liquid AI releases LFM3 multimodal models
Hugging Face Blog · October 27, 2026 · Related
What happened next
- 4llama.cpp adds LiquidAI LFM3 model support
llama.cpp Releases · October 28, 2026 · Same story
Follow this story
Open the full story →llama.cpp b11747 adds ROCm 10 and CUDA 13 support
3 developments
- Oct 20 · llama.cpp Releases
llama.cpp b11747 adds ROCm 10 and CUDA 13 support - Oct 28 · llama.cpp Releases
llama.cpp adds LiquidAI d1 models and CUDA 13 support↳ llama.cpp adds native support for LiquidAI d1-2B and d1-omni-2B models - Oct 28 · llama.cpp Releases
llama.cpp adds LiquidAI LFM3-Audio and Omni support (This article)↳ llama.cpp adds native conversion for LiquidAI LFM3-Audio and Omni architectures with specific encoder convolution handling
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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