Intel just listed the Arc Pro B70 on its official product page, a strong signal that the 32GB VRAM professional GPU is close to hitting shelves.
The spec that matters here: 32 gigabytes of video memory. For anyone running large language models locally on their own hardware instead of paying for cloud API calls, VRAM (the memory on your graphics card that holds the model weights during inference) is the single biggest bottleneck. Most consumer Nvidia cards top out at 16GB or 24GB. The RTX 5090 offers 32GB but carries a $2,000 price tag and has been nearly impossible to buy at retail. AMD's Radeon RX 9070 XT sits at 16GB.
Intel's play is interesting because the Arc Pro line targets workstation users, not gamers. That means the B70 should prioritize memory capacity and compute stability over raw frame rates. For local AI work, that tradeoff is exactly right. You do not need 120 FPS rendering. You need enough VRAM to load a 30-billion-parameter model without quantizing it down to the point where output quality degrades.
The big unknown is software support. Nvidia's CUDA dominates the local LLM toolchain. Most frameworks like llama.cpp and vLLM work best on Nvidia hardware, with AMD ROCm support improving but still behind. Intel's oneAPI and SYCL stack has been gaining ground, and recent llama.cpp builds do include Intel GPU support, but the experience is not as polished. A 32GB card at a competitive price means nothing if the software friction keeps users away.
Pricing has not been announced. Intel's current Arc Pro A60 (16GB) sells around $350-400. If the B70 lands anywhere near the $500-700 range with 32GB, it would undercut Nvidia's professional lineup significantly and give budget-conscious AI tinkerers a real alternative. No launch date has been confirmed, but products appearing on Intel's official site typically ship within weeks.