Models & Labs
llama.cpp adds LiquidAI d1 models and CUDA 13 support
llama.cpp Releaseshigh confidence
Why it matters
- →LiquidAI d1 models are now available for local inference via llama.cpp.
- →CUDA 13 binaries allow users to leverage newer NVIDIA driver features immediately.
- →KleidiAI support is temporarily disabled, requiring users to check future builds for Apple Silicon optimization.
llama.cpp release b11945 adds native support for LiquidAI’s d1-2B and d1-omni-2B models, integrating them into the GGUF format. The update includes pre-built binaries for CUDA 13 (version 13.4) on Linux and Windows, alongside existing CUDA 12 builds. Apple Silicon KleidiAI support is currently disabled in this release. The update also contains minor refactoring to remove no_batching logic.
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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
- 1llama.cpp b11027 adds CUDA 13 and ROCm 10 builds
llama.cpp Releases · September 18, 2026 · Same story
- 2llama.cpp b11146 adds CUDA 13 and Snapdragon support
llama.cpp Releases · September 24, 2026 · Same story
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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 (This article)↳ 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↳ llama.cpp adds native conversion for LiquidAI LFM3-Audio and Omni architectures with specific encoder convolution handling
More from llama.cpp Releases
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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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