edp1096/Huihui-Qwen3.8-Flash-Next-abliterated-NVFP4-QAD

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Base: Conversion: DQ(LIL QAD5500) + Huihui BF16 - Qwen BF16, followed by BF16 rounding and ModelOpt requantization. The QAD base is revision 6909a5bed089a48fa07e956d3915af2537de9368; the official Huihui BF16 source is 298f94632b784e26a7fe576114f82066689d5baa, compared with Qwen BF16 de4b8e4d43b917e7706784d8bb445c9af86a3540. The audit identified 144 changed tensors, covering 24,672 matrices in native Hugging Face order. Original LIL activation scales are retained without new activation calibration. Requantization error remains; preservation of LIL benchmark scores is not claimed. See transfer-manifest.json and bf16-audit.json. Validated on DGX Spark TP1 with SGLang: 64K and 1M actual-input retrieval, language/code/tool/vision probes, and post-long-context generation passed. The 1M test processed 1,048,435 uncached input tokens. See runtime-qualification.json. Recipe example (uses the locally built qualification image; its immutable image ID is recorded in runtime-qualification.json): Qwen Community License 1.0. Credits: Qwen, local-inference-lab, Huihui, NVIDIA ModelOpt, SGLang, hashd1ve, B12X, eugr. local-inference-lab/Qwen3.8-Flash-Next-NVFP4 is a mixed-precision model distilled from Qwen/Qwen3.8-Flash-Next using quantization-aware distillation (QAD). The student is trained against the…

edp1096/Huihui-Qwen3.8-Flash-Next-abliterated-NVFP4-QAD on Hugging Face A short preview, not the full document.

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  1. Huihui-Qwen3.8-Flash-Next-abliterated-NVFP4-QAD
  2. Sources and license
  3. Model Description
  4. What's quantized
  5. Quantization-aware distillation
  6. Training data
  7. Activation calibration
  8. Requirements
  9. Evaluation

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edp1096/Huihui-Qwen3.8-Flash-Next-abliterated-NVFP4-QAD is a task-unspecified model repository published by edp1096 on Hugging Face. A library was not reported.

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Created
2026-09-21T06:33:06.000Z
Last modified
2026-09-21T06:33:06.000Z

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