AI Briefingllama.cpp, MTP VRAM Savings Update
Key point
llama.cpp has applied an update that reduces VRAM usage by processing the KQ mask in f16 when using Flash Attention.
Details
An update has been applied to llama.cpp that improves VRAM efficiency by reserving the KQ mask in f16 instead of f32 when using Flash Attention (FA).
Previously, even when FA was used, the KQ mask was reserved in f32 and then converted to f16 when passed to the backend. In this process, the unused f32 mask occupied the compute buffer, causing unnecessary VRAM consumption.
With this change, the following VRAM savings can be expected in MTP (Multi-Token Prediction) environments:
- With -ub 2048 setting: about 1.2GB saved
- With -ub 512 setting: about 300MB saved
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