ByteShape drops hardware-tuned Qwen 3.5 9B quants

ByteShape's "ShapeLearn" approach highlights a critical reality for local LLM deployment: generic quantization is a bottleneck on heterogeneous consumer hardware.

• –GPU quants (like the 4.43 bpw "GPU-6" variant) maintain 99% quality while ensuring stable performance across RTX 50, 40, and 30-series cards.
• –CPU inference is surprisingly "messy," with Intel and AMD chips requiring different bit-depth variants to achieve optimal speed/quality trade-offs.
• –The inclusion of Raspberry Pi 5 benchmarks serves as a realistic warning for edge developers, proving that 9B dense models remain painfully slow on low-power ARM devices.
• –By providing interactive graphs and 10+ specific variants, ByteShape is moving toward "hardware-aware" model distribution rather than one-size-fits-all weights.