llama.cpp b9950 adds unit test for batch processing with expanded platform support
New version b9950 improves batch inference reliability on CPU, GPU, and mobile. Available now.
The llama.cpp team released version b9950, a maintenance update that adds a dedicated unit test for the llama-batch feature. This test validates batch inference logic, catching regressions early and improving reliability for developers running multiple prompts simultaneously. The release includes builds for a wide range of hardware: macOS Apple Silicon (both standard and KleidiAI-accelerated), macOS Intel, iOS, Linux on x64 and arm64 with Vulkan, ROCm 7.2, OpenVINO, SYCL FP32/FP16, Android arm64, and Windows on x64 and arm64 with CUDA 12/13, Vulkan, OpenCL Adreno, and HIP.
While no new model architectures or performance boosts are mentioned, the focus on testing indicates growing maturity as llama.cpp serves production workloads. The commit is signed with a verified GPG key, ensuring authenticity. This release is particularly relevant for developers deploying LLMs locally on diverse hardware, as batch processing is essential for chatbots, RAG pipelines, and multi-query agents running on consumer or edge devices.
- llama.cpp v3.0.0-b9950 adds unit test for llama-batch to ensure reliable multi-prompt inference
- Builds cover 15+ platform combinations: Apple Silicon, Linux (x64/arm64), Windows (CPU/GPU), Android, and openEuler
- Includes GPU backends: Vulkan, ROCm 7.2, CUDA 12/13, OpenCL Adreno, SYCL, HIP, and OpenVINO
Why It Matters
llama.cpp enables efficient local LLM inference; batch test ensures reliability for production multi-query apps across consumer hardware.