Qwen3.8-27B-nvfp4qat-NInfer
The repository contains a QAT-sourced NVFP4 weight profile of Qwen/Qwen3.8-27B in the native NInfer `.ninfer` artifact format, with the z-lab/Qwen3.8-27B-DFlash2 block-diffusion speculative drafter embedded in the same image. It runs on NInfer **v3** engines — Text and MTP components through format/shape routes the upstream runtime already implements, the optional NVFP4-encoded DFlash2 companion through the fork's runtime support. It is not a Transformers checkpoint, Safetensors distribution, or GGUF file. This is a fourth weight profile for the existing `qwen3_8_27b` target — a peer of the official `groupwise-int` and `nvfp4` profiles and of the fork's fuller-requant `nvfp4full` profile. The Text weight stack is copied **word-for-word** from QUASAR-QAT/Qwen3.8-27B-QUASAR-NVFP4 — a quantization-aware-trained checkpoint (QUASAR loss-aware NVFP4 distillation against the frozen BF16 teacher, arXiv 2608.13966): - every one of the 496 text linear layers is NVFP4 (W4A4) — attention, gated-delta-net, and MLP alike, with no high-precision exceptions; - the QAT factory quantizes per site, so every constituent tensor of a fused parent shares one weight and input global scale; the converter enforces that sharing before copying a word, and the site input divisors ride the artifact directly; - the GDN control projections are decoded from their QAT NVFP4 words to the BF16 control parent the engine consumes.
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The repository contains a QAT-sourced NVFP4 weight profile of Qwen/Qwen3.8-27B in the native NInfer `.ninfer` artifact format, with the z-lab/Qwen3.8-27B-DFlash2 block-diffusion speculative drafter embedded in the same image. It runs on NInfer **v3** engines — Text and MTP components through format/shape routes the upstream runtime already implements, the optional NVFP4-encoded DFlash2 companion through the fork's runtime support. It is not a Transformers checkpoint, Safetensors distribution, or GGUF file. This is a fourth weight profile for the existing `qwen3_8_27b` target — a peer of the official `groupwise-int` and `nvfp4` profiles and of the fork's fuller-requant `nvfp4full` profile. The Text weight stack is copied **word-for-word** from QUASAR-QAT/Qwen3.8-27B-QUASAR-NVFP4 — a quantization-aware-trained checkpoint (QUASAR loss-aware NVFP4 distillation against the frozen BF16 teacher, arXiv 2608.13966): - every one of the 496 text linear layers is NVFP4 (W4A4) — attention, gated-delta-net, and MLP alike, with no high-precision exceptions; - the QAT factory quantizes per site, so every constituent tensor of a fused parent shares one weight and input global scale; the converter enforces that sharing before copying a word, and the site input divisors ride the artifact directly; - the GDN control projections are decoded from their QAT NVFP4 words to the BF16 control parent the engine consumes.
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