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An ex-leader from Alibaba's Qwen AI team shares a plot twist on Twitter, hinting at a potential change or announcement in the AI industry.
The article explores using a ZIMA Board 2 with an RTX 2000 ADA GPU as an affordable self-contained setup for running the Qwen 3.8 27b AI model, comparing it with alternatives like the Mac Mini M5.
The article describes testing the Qwen3.8-27B AI model with different quantizations and settings to recreate images as SVG, aiming to develop a benchmark resistant to benchmaxxing. Preliminary results indicate that high reasoning effort and specific cache configurations optimize performance.
The author has updated their NInfer fork with rk2v4-e8 quantization for the KV cache, enabling up to 250-350K tokens context on a single RTX 4090 without system RAM spill and with optimizations for faster generation speeds.