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Ling-3.0 (BailingMoE3) is now officially supported in llama.cpp, with benchmarks on Intel Arc B580 showing efficient local inference including 128K context in 12GB VRAM.
A showcase of a personal local AI inference build featuring Intel Arc B140 GPUs and custom hardware, running llama.cpp with SYCL back-end on Ubuntu.
Intel reveals the Arc Pro B70 graphics card box and a 3D model of the card, indicating a forthcoming product launch.
The MSI Claw 8 EX AI+ is a powerful handheld gaming PC with Intel's Arc GPU, excellent ergonomics, and a premium design, but its high price and lack of OLED display are drawbacks.
A user successfully ran nvfp4 quantization on Intel Arc B70s GPUs, achieving nearly double speed and higher accuracy compared to their best int4 configuration, challenging hardware-specific format assumptions.
A llama.cpp PR significantly improves prompt processing speed on Intel ARC GPUs, with benchmark showing speed increase from 245t/s to 462t/s on a B580. The improvement currently works for F16 KV quantization, with plans to support other quants.
A pull request for llama.cpp ports multi-column MMVQ from CUDA to SYCL, achieving approximately 45% speculative decoding speedup on Intel Arc GPUs.
Qwen3.6-27B-FP8 model is now running on Intel Arc Pro B70 GPUs at ~50 tok/s with a vLLM bug fix, marking a significant milestone for Intel GPU local AI inference.
Community benchmark shows Intel Arc Pro B70 averages ~71% slower prompt processing and ~54% slower token generation than RTX 3090 under llama.cpp, with SYCL backend sometimes beating Vulkan on the same card.