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llama.cpp b11005 fixes Gemma graph splits
llama.cpp Releaseshigh confidence
Why it matters
- →Fixes a specific graph fragmentation issue that degraded inference speed on AMD/Intel hardware.
- →Improves efficiency for Gemma models by keeping computation on the accelerator rather than CPU.
- →Maintains broad hardware support including CUDA 13 and ROCm 10.0 binaries.
llama.cpp has released version b11005, addressing a performance regression in the Hexagon backend that affected Gemma models. The update modifies rope probe handling to accept zeroed parameters, preventing the runtime from incorrectly offloading frequency calculations to the CPU. This change reduces graph fragmentation during decoding, specifically cutting splits in half for certain Gemma configurations. The release includes standard binaries for macOS, Linux, Windows, and Android across CUDA 12/13, ROCm 10.0, and Vulkan backends.
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llama.cpp b11000 fixes critical RCE in server
This release patches a critical remote code execution vulnerability in the llama.cpp server that allowed unauthenticated attackers to hijack memory via dangling pointers. The flaw stemmed from caching compute graphs that referenced freed buffers, enabling heap corruption and arbitrary code execution through subsequent tensor commands. By discarding cached graphs when buffers are freed, the fix forces a safe fallback to full recomputation without changing the API. This is a vital security update for anyone running the llama.cpp server remotely, closing a direct path to system compromise.
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