{"slug": "the-llama-cpp-and-vllm-projects-move-insanely-fast-do-we-have-a-good-grasp-on-on", "title": "The llama.cpp and vLLM projects move INSANELY fast. do we have a good grasp on how good tensor-parallel inference on Intel Arc is at the end of Aug 2026?", "summary": "As of late August 2026, the llama.cpp and vLLM projects are advancing rapidly, but community members report that the most recent information on tensor-parallel inference for Intel Arc GPUs remains a Reddit post from earlier in the year, which highlighted a merged PR for TP SYCL in llama.cpp. Users are seeking updated performance benchmarks, particularly for running Qwen3.6/8-27B on dual Arc Pro B65 GPUs, with some considering switching from two 16GB 5060Tis to gain sufficient VRAM for reasonable quantization without quantizing KV cache.", "body_md": "this is the most recent stuff I can find: [Reddit](https://www.reddit.com/r/LocalLLaMA/comments/1ufctc8/tensor_split_fix_for_intel_gpus_llamacpp_release/)\n\neverything more recent I find just ends up linking back to that post. which like, sure, I get it, that was where folks pointed out the PR for TP SYCL that got merged into llama.cpp. I just want to know if folks around here are running it and whether or not you’ve seen improvements in performance over the past two months, especially on everyone’s favorite, Qwen3.6/8-27B. I am slowly leaning in the direction of selling my two 16GB 5060Tis and purchasing a couple of Arc Pro B65s (if I can find them) in order to have the VRAM to run that model specifically at a reasonable quant without quantizing kv.", "url": "https://wpnews.pro/news/the-llama-cpp-and-vllm-projects-move-insanely-fast-do-we-have-a-good-grasp-on-on", "canonical_source": "https://forum.level1techs.com/t/the-llama-cpp-and-vllm-projects-move-insanely-fast-do-we-have-a-good-grasp-on-how-good-tensor-parallel-inference-on-intel-arc-is-at-the-end-of-aug-2026/254649#post_1", "published_at": "2026-08-29 22:12:21+00:00", "updated_at": "2026-08-29 22:19:40.005033+00:00", "lang": "en", "topics": ["large-language-models", "ai-infrastructure", "ai-tools"], "entities": ["llama.cpp", "vLLM", "Intel Arc", "Arc Pro B65", "Qwen3.6/8-27B", "5060Ti"], "alternates": {"html": "https://wpnews.pro/news/the-llama-cpp-and-vllm-projects-move-insanely-fast-do-we-have-a-good-grasp-on-on", "markdown": "https://wpnews.pro/news/the-llama-cpp-and-vllm-projects-move-insanely-fast-do-we-have-a-good-grasp-on-on.md", "text": "https://wpnews.pro/news/the-llama-cpp-and-vllm-projects-move-insanely-fast-do-we-have-a-good-grasp-on-on.txt", "jsonld": "https://wpnews.pro/news/the-llama-cpp-and-vllm-projects-move-insanely-fast-do-we-have-a-good-grasp-on-on.jsonld"}}