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David Hendrickson
@TeksEdge
CEO & Founder | PhD | Startup Advisor | @Columbia | Author Generative Software Engineering | ๐Ÿ”” Follow for AI & Vibe Coding Tips ๐Ÿ‘‡
๊ฐ€์ž… July 2023
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Intel's 32GB Arc Pro B70 finally got a proper Qwen3.8-27B Local AI workout. So this is why the 32GB VRAM is important, even from an Intel GPU. Here is Gigazine's setup. Windows 11 using Unsloth Desktop + llama.cpp ... ๐Ÿง  Qwen3.8-27B Q4_K_XL ๐Ÿ’พ 30.0GB VRAM + ~1GB shared RAM ๐Ÿš€ 23.4 tps Then they tried Q8: ๐Ÿง  Qwen3.8-27B Q8_K_XL ๐Ÿ’พ 30.2GB VRAM + ~1.5GB shared RAM โšก 15.9 tps That's a full 27B-class model running at very usable speeds on an Intel GPU. And also tested text-to-image models. ๐ŸŽจ Z-Image-Turbo 1024ร—1024 / 8 steps โžก๏ธ ~5.3 sec/image after warmup ๐ŸŽฅ MiniMax H3 video also ran โ€ฆbut these are much slower, demonstrating where Nvidia's more mature AI software stack still matters. The hardware setup... ๐ŸŽฎ Arc Pro B70 ๐Ÿ’พ 32GB GDDR6 โšก 608 GB/s bandwidth ๐Ÿ”Œ 230W And here's the interesting value angle. In Japan, the tested ASRock B70 was selling for: ๐Ÿ’ฐ ยฅ298,054 while many RTX 5090s were selling above: ๐Ÿ’ฐ ยฅ900,000 โš ๏ธ That's Japan-specific street pricing, NOT a universal B70-vs-5090 price comparison. But THIS is why the B70 interests me for Local AI. It won't beat a 5090 but it's giving you 32GB of VRAM at a much lower entry point. 23.4 tok/s on Qwen3.8-27B Q4 good enough for you? ๐Ÿ”— GIGAZINE review in ALT
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