Models & Labs
New Runtime-Learning Accelerator for LLM Inference
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Why it matters
- →This advancement could significantly improve the efficiency of LLM applications, making them more responsive and effective for users.
The AdapTive-LeArning Speculator System (ATLAS) enhances LLM inference speed by adapting to workloads, achieving 500 TPS on DeepSeek-V3.1, which is a 4x improvement over baseline performance without manual tuning.
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llama.cpp b12029 adds CUDA 13 and Snapdragon support
This release quietly cements llama.cpp as the universal inference runtime by finally supporting NVIDIA's latest CUDA 13 stack alongside AMD's ROCm 10.0. The inclusion of native builds for Linux arm64 with Snapdragon chips, covering CPU, Adreno GPU, and Hexagon NPU, signals a serious push into mobile edge deployment. While Apple Silicon KleidiAI is disabled in this specific build, the broader hardware coverage means developers no longer need to compile from source for most modern accelerators. It’s less about new features and more about removing friction for anyone running local models on bleeding-edge or diverse hardware.
llama.cpp Releases
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