이전 버전입니다. 현재 최신 버전은 b9994입니다. llama.cpp b9994 · 출시일:
설치 파일 b10730
| 아키텍처 | 형식 | 설치 범위 | 파일 크기 | 다운로드 | SHA256 |
|---|---|---|---|---|---|
| 64비트 | ZIP → 포터블 | — | — | github.com | VirusTotal |
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릴리스 노트
qwen4exp: sum the indexer heads by slices (#28023)
- qwen4exp: sum the indexer heads by slices
The head reduction went through a transpose and a sum_rows over ne[1],
which left sum_rows with ne0 = 4, one block per row for a four element
reduction, and the transpose copied the whole block by token surface
twice on the way in.
The heads are adjacent on ne[1], so each one is a strided view and the
sum is a short chain of adds.
RTX PRO 6000, Qwen3.8-Flash-Next UD-Q4_K_XL, fa on, 55k context, warm
runs on top of #28011:
prompt processing 2170 -> 2366 t/s
Generation is unaffected. The removed work scales with n_blocks by
n_tokens, so the gain grows with context and with ubatch size.
- qwen4exp: drop the redundant cont on the indexer query
rope returns a freshly allocated, contiguous tensor, so the reshape that
feeds the matmul does not need a copy. ggml_reshape_3d asserts
contiguity, so a layout that would need the cont cannot slip through
silently.
Greedy output is unchanged token for token.
Address review from @ggerganov
Website:
- https://llama.app
Attestations:
- https://github.com/ggml-org/llama.cpp/attestations/44321551
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 (ROCm 7.14)
- 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 13.3 DLLs
- Windows arm64 (CUDA 13) (preview) - CUDA 13.4 DLLs
- Windows x64 (Vulkan)
- Windows x64 (OpenVINO)
- Windows x64 (SYCL)
- Windows x64 (ROCm 7.14)
openEuler:
- DISABLED
- openEuler x86 (310p)
- openEuler x86 (910b, ACL Graph)
- openEuler aarch64 (310p)
- openEuler aarch64 (910b, ACL Graph)
UI:
- UI