qwen35-2b-webgpu — GPTQ-int4 weights

Custom GPTQ-int4 quant (group 32, byte-sliced nibbles, single tied q4 copy of the 248k-vocab embedding serving both the gather and the logits cascade) of Qwen/Qwen3.5-2B (text part), in the wire format of the qwen35-2b-webgpu browser runtime.

The first hybrid gated-DeltaNet + gated-attention LLM running in the browser — pure WebGPU, hand-written WGSL kernels (chunked WY-representation delta-rule prefill, fused recurrent decode step, f32 state), no ONNX / transformers.js / GGUF.

• ~1.07 GB; GPTQ calibrated on chat-formatted passages.
• The runtime is verified against a PyTorch f32 reference (per-layer rms, cascaded argmax bit-exact vs the exact-logits path).

Try it: https://huggingface.co/spaces/borkiss/qwen35-2b-webgpu-demo · run /web/bench.html on your GPU and share the .log.