Model Releases
b10997
HIP: broaden MoE ncols_opt tile heuristic on RDNA3.5 architecture (#28935) It's found the MoE ncols_opt tile heuristic needs to be broadened to include the RDNA3.5 architecture. The code change is imp
HIP: broaden MoE ncols_opt tile heuristic on RDNA3.5 architecture (#28935) It's found the MoE ncols_opt tile heuristic needs to be broadened to include the RDNA3.5 architecture. The code change is implemented in ggml/src/ggml-cuda/mmq.cu and just change the GGML_CUDA_CC_IS_RDNA3_0 to GGML_CUDA_CC_IS_RDNA3 in the condition. The dense dispatch logic remains unchanged. The Test machine configuration we used is AMD Radeon 8060S, gfx1151 (RDNA3.5), 20 CU, wave32 AMD Ryzen AI MAX+ 388, 8C/16T, 23.79 GB RAM we complete the Correctness verification and performance evaluation as follows: test-backend-ops test -b ROCm0 -o MUL_MAT -p type_a=<q4_K|q5_K|q4_0|q5_0> test-backend-ops test -b ROCm0 -o MUL_MAT_ID -p type_a=<q4_K|q5_K|q4_0|q5_0> all pass: MUL_MAT 64/64, 29/29, 48/48, 14/14; MUL_MAT_ID 84/84, 3/3, 74/74, 3/3 Performance result on target machine: LFM2.5-8B-A1B-UD-Q4_K_M (Q4_K MoE) +16.198% [+12.704, +19.799] 8/8 Qwen1.5-MoE-A2.7B-Q2_K (Q2_K MoE) +6.189% [ +5.245, +7.141] 8/8 pooled (16 pairs) +11.081% [ +7.972, +14.279] 16/16 Token generation (tg128) is unchanged on the Q4_K MoE model and +2.188% [+0.905, +3.488] on the Q2_K one. Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/47864136 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (arm64, KleidiAI enabled) DISABLED macOS Intel (x64) iOS XCFramework Linux: Ubuntu x64 (CPU) Ubuntu arm64 (CPU) Ubuntu s390x (CPU) Ubuntu x64 (Vulkan) Ubuntu arm64 (Vulkan) Ubuntu x64 (CUDA 12) - CUDA 12.8 libraries Ubuntu x64 (CUDA 13) - CUDA 13.3 libraries Ubuntu arm64 (CUDA 13) - CUDA 13.3 libraries Ubuntu x64 (ROCm 10.0) Ubuntu x64 (OpenVINO) Ubuntu x64 (SYCL FP32) Ubuntu x64 (SYCL FP16) Android: Android arm64 (CPU) Windows: Windows x64 (CPU) Windows arm64 (CPU) Windows arm64 (OpenCL Adreno) Windows x64 (CUDA 12) - CUDA 12.4 DLLs Windows x64 (CUDA 13) - CUDA 13.4 DLLs Windows arm64 (CUDA 13) - CUDA 13.4 DLLs Windows x64 (Vulkan) Windows x64 (OpenVINO) Windows x64 (SYCL) Windows x64 (ROCm 10.0) openEuler: DISABLED openEuler x86 (310p) openEuler x86 (910b, ACL Graph) openEuler aarch64 (310p) openEuler aarch64 (910b, ACL Graph) UI: UI
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Source: llama.cpp Releases | 2026-09-16