llama.cpp Update Boosts Intel Inference Performance
pmttyji · reddit · 2026-07-15
llama.cpp recently merged a batch of updates tailored for SYCL / Intel, focusing on performance and operator support:
- Flash Attention / SDPA optimizations via the oneDNN graph API bring significant speedups on Xe2; using Qwen3.6-27B-Q80 as an example, prefill speed increased by 1.21x at p=512 and 4.26x at p=80k.
- Additional updates include: adjusting the minimum buffer size for USM system allocation, supporting OP XIELU, adding an fp16 conv2ddw kernel, and fixing precision issues with getrows across multiple quantization formats.
Overall, this is a classic local inference stack optimization, enhancing both Intel platform viability and long-context prefill performance.
More from Infra
- LLM Serving Metrics Thread: Why TPOT and Uptime Make or Break User Experience — abhijithneil · 2026-09-11
- PlanetScale launches sharded Postgres: 768 servers acting as one, 1PB scale — dhruv2038 · 2026-09-11
- Can a 7900 XTX 24GB run Qwen locally? Reddit seeks ROCm tok/s benchmarks — thenomadexplorerlife · 2026-09-11
- RTK Terminal Compression Cuts Tokens but Leaves Your AI Coding Bill Unchanged — Bartaseth · 2026-09-11
- SF Compute founder: buying compute is 'an absolutely awful experience' right now — IgorCarron · 2026-09-11
- SmolVM open-sources persistent computer infrastructure for agents that outlive chat sessions — aniketmaurya · 2026-09-11