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llama.cpp v0.2.0 pre‑release adds Hexagon CPU optimizations

The open‑source LLM runner updates its Hexagon backend for faster concat operations on Snapdragon chips.

NoteOossa1 min read

The ggml‑org/llama.cpp project published a pre‑release build (tag b11272) on 30 Sept 2026. It adds a Hexagon‑specific optimization for the concat operation, which is a common step in language‑model inference. The change reduces packet overhead and uses a faster division routine, speeding up the hot loop that moves data around. The update is part of a broader set of builds for many platforms, including Android Snapdragon devices with Hexagon NPUs.

Why it matters

It makes running LLMs on Snapdragon phones noticeably faster, lowering latency for on‑device AI tasks.

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Sources & references

#SourceOutletDateKey takeaway
1ggml-org/llama.cpp b11272 ↗llama.cppSep 30, 2026<details open> hexagon: optimize concat op (#29673) * hex-concat: reduce pkts in gather/transpose hot loop gather directly into dst buffer,

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