Intel Arc Pro B70chat_bubble_outlineFrom real comments

VRAM and price make it a standout value for local AI. Commenters repeatedly cite the 32GB VRAM at roughly $950-1000 as the card's biggest draw, calling it the 'sweetspot' for local LLM work and far cheaper than AMD's R9700 or enterprise Nvidia cards. Multiple buyers moved from 24GB cards or canceled AMD orders after finding this price-to-VRAM ratio. Power efficiency is also praised, with systems drawing well under Nvidia equivalents while running similar workloads.

Performance is strong on MoE models but weak on dense models and long context. Users report 80-100+ t/s on MoE models like Qwen3.6 35B A3B and Gemma 4 using llama.cpp/SYCL or vLLM, and pipeline-parallel multi-GPU scaling works well. However, dense models run only 15-20 t/s, prompt processing is painfully slow, and performance degrades badly above roughly 65k context. Some found an RTX 5070Ti or 3090 outperformed it on comparable models.

Software stack is immature and setup is a real hurdle. Many describe SYCL, vLLM, and driver support as unfinished, requiring manual llama.cpp builds, docker images lagging a year behind vLLM main, and multi-GPU support called 'atrocious.' Windows users seem to struggle more than Linux users. Firmware/driver updates have also broken features like SR-IOV VF counts without official response from Intel.