The llama.cpp project has released several pre-release versions, including b12207, which significantly improves performance for Zamba2-like architectures by optimizing the SSM_SCAN kernel for a state size of 64. This optimization led to a ~35% throughput increase for Zamba2-7B-Instruct on GPUs, though some scan calls still fall back to the CPU for reasons yet to be determined. Other recent releases, such as b12206 and b12201, address issues with MoE caching and speculative decoding, ensuring better efficiency and stability across various platforms including macOS, iOS, Linux, Android, and Windows. AI
IMPACT Improves inference speed and stability for various LLM architectures on consumer hardware.
RANK_REASON Multiple pre-release updates to an open-source inference library, including performance optimizations and bug fixes.
Read on llama.cpp — Releases →
- b12201
- b12202
- DeepSeek V4
- DeepSeek V4.1
- GGML_PREC_BF16
- GGML_PREC_F32
- GLM4
- llama.cpp
- MiniMax-M3
- Qwen3-TTS
- android
- Claude Sonnet
- ggml-cuda
- iOS
- KleidiAI
- Linux
- macOS
- Microsoft Windows
- moe-cache
- OpenEuler
- Sargentmajord
- SSM_SCAN
- Zamba2
- Zamba2-7B-Instruct
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