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Open Source

llama.cpp b9490 Release Expands Platform Support

llama.cpp Releases·June 4, 2026·high confidence

Why it matters

  • →Expanding platform support increases accessibility for developers across different systems.
  • →Enhanced GPU support on Windows and Linux improves performance for AI tasks.
  • →Disabling certain features indicates ongoing refinement and focus on stability.

The b9490 release of llama.cpp has been announced, focusing on expanding platform support across various operating systems. Notably, the update includes Vulkan and ROCm 7.2 support for Ubuntu, and CUDA 12 and 13 DLLs for Windows, enhancing GPU performance. However, some features like KleidiAI on macOS Apple Silicon and SYCL on Windows remain disabled. This release highlights llama.cpp's ongoing efforts to cater to a wide range of hardware configurations.

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llama.cpp b9489 release enhances CUDA support

The b9489 release of llama.cpp brings notable improvements for CUDA users, specifically by reserving space for quantized key-value caches at startup. This update also addresses previous feedback and removes certain assertions in the ggml-cuda.cu file, enhancing the CUDA experience. While it doesn't introduce new models or quantization techniques, the release continues to refine the platform's compatibility across macOS, Linux, and Windows. With ROCm 7.2 and KleidiAI support, llama.cpp is becoming a more robust tool for developers working with CUDA and other environments. This iteration is a step towards making llama.cpp a more versatile and efficient tool for AI development.

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llama.cpp b9493 Release Expands Platform Support

The b9493 release of llama.cpp continues to broaden its platform reach, notably integrating ROCm 7.2 for Ubuntu x64, which offers better support for AMD GPU users. Although features like KleidiAI on macOS Apple Silicon remain inactive, the update emphasizes extending functionality across various systems, including Vulkan support for both Ubuntu and Windows. While no new models are introduced, this release strengthens llama.cpp's role as a versatile inference runtime across multiple operating systems. Developers can now take advantage of improved GPU support, making it a more inclusive tool for those working outside the NVIDIA ecosystem.

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