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llama.cpp adds faster SYCL attention for quantized caches

Release b11980 adds an Intel GPU kernel for small-batch decoding with q4_0 and q8_0 KV caches; prompts still use existing kernels.

NoteBy Published by Oossa: 1 min read

The llama.cpp b11980 release adds a SYCL flash-attention kernel for decoding with q4_0 and q8_0 quantized key-value caches. It handles batches of 1 to 31 query tokens, avoiding scalar dequantization or converting the full cache to f16 for each call.

The release notes report that on an Intel Arc B580, Llama 3.1 8B Q4_K_M with a q4_0 cache reached 54.2 tokens per second at a 16K context, up from 31.3. That result is for one stated setup; prompt processing remains on the existing kernels, and the new kernel can be disabled with GGML_SYCL_FA_DPAS=0.

Why it matters

For people decoding on an Intel Arc B580 with quantized caches, this could mean faster token generation in the tested setup; the release gives no evidence that prompt processing or other hardware will speed up similarly.

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