Changelog
- Updated the llama.cpp base through upstream commit
74ce15741. Notable inherited changes include Qwen3-TTS, DeepSeek V4 and DSpark, MTP support for GLM-4.7-Flash, GLM-5.2, Qwen3-Next, and DeepSeek V3.2, router LRU scheduling, initial Docker tool isolation, working-directory and filesystem tools in the server and Web UI, speculative metrics, and broad CUDA, Metal, Vulkan, SYCL, WebGPU, multimodal, conversion, and UI updates. ggml is now 0.19.0 and the RPC protocol is 5.0.1. - Fixed HIP/ROCm KVarN routing. Precision tails remain on native attention instead of allocating a context-sized F16 materialization, unsupported AMD matrix shapes fall back to portable direct-record attention, and split/vector decode is selected only for supported AMD routes. Capability reporting, route telemetry, memory accounting, and Vulkan RoPE/offset checks now match the implemented kernels.
- Made KVarN and precision-tail memory fitting exact and bounded. The CLI, fit probes, and final context share one immutable tail request; invalid group specifications fail context creation; Vulkan uses backend workspace planners during fit; and final no-allocation validation restarts fit from pristine inputs or fails deterministically. Vulkan also gains a native one-softmax route for standard quantized bodies with F16/BF16 history and current segments.
- Reworked prompt-cache reuse across standard, recurrent, and KVarN state. Live and RAM candidates share one safe-prefix planner and transactional target/draft/speculative restore; failures leave live state unchanged. Self-contained sequence-selective checkpoints preserve precision tails and repeatable RAM restores. Durable KVarN reuse remains descriptor-aligned, while standard/recurrent batching and explicit GPU-fit behavior remain upstream-compatible. Unified KVarN slots now borrow shared capacity instead of using fixed stripes, and full state remaps live stage rows across slot counts; compact sparse reads and batched checkpoint transfers improve multi-slot
--cache-ramprefill throughput. - Fixed CUDA KVarN attention at both ends of the hardware range. Pre-Turing portable attention now passes architecture-neutral capability checks and exports the softmax metadata required to merge exact tails correctly. Split and vector decode share a once-per-device dynamic shared-memory opt-in, preventing configuration failures and extending the vector combine path beyond the default 48 KiB limit. KVarN MMA warning fixes keep fatal-warning builds clean.
- Restored
status.argsandstatus.presetin router/v1/modelsresponses for upstream-compatible clients while continuing to strip sensitive options.
macOS:
Linux:
- Ubuntu x64 CPU
- Ubuntu arm64 CPU
- Ubuntu x64 CUDA 12.4
- Ubuntu x64 CUDA 13.1
- Ubuntu x64 Vulkan
- Ubuntu x64 ROCm 7.2
- Ubuntu x64 SYCL
Windows:
- Windows x64 CPU
- Windows x64 Vulkan
- Windows x64 SYCL
- Windows x64 CUDA 12.4 - DLLs
- Windows x64 CUDA 13.1 - DLLs
- Windows x64 HIP
Docker:
- CPU:
docker pull ghcr.io/anbeeld/beellama.cpp:server-cpu-v0.4.3 - CUDA:
docker pull ghcr.io/anbeeld/beellama.cpp:server-cuda-v0.4.3 - CUDA 12:
docker pull ghcr.io/anbeeld/beellama.cpp:server-cuda12-v0.4.3 - CUDA 13:
docker pull ghcr.io/anbeeld/beellama.cpp:server-cuda13-v0.4.3 - ROCm:
docker pull ghcr.io/anbeeld/beellama.cpp:server-rocm-v0.4.3 - Vulkan:
docker pull ghcr.io/anbeeld/beellama.cpp:server-vulkan-v0.4.3 - SYCL:
docker pull ghcr.io/anbeeld/beellama.cpp:server-sycl-v0.4.3