Qwen3.8-Flash-Next-NVFP4-MXFP8-CSF-QAD
This model is based on Qwen3.8-Flash-Next-NVFP4-MXFP8-CSF-QAD by Local Inference Lab, Inc., a non-profit organization, available at https://huggingface.co/local-inference-lab/Qwen3.8-Flash-Next-NVFP4-MXFP8-CSF-QAD. Qwen3.8-Flash-Next-NVFP4-MXFP8-CSF-QAD is licensed under the Local Inference Lab License, Version 1.0.
Multimodal checkpoint with QAD decoder weights, losslessly compressed routed-expert block scales, MXFP8 attention, NVFP4 MTP routed experts, and mixed-precision vision weights.
| Component | Stored precision |
|---|---|
| Decoder routed experts | QAD NVFP4; E2M1 values, E4M3 block scales, FP32 global/input scales |
| Decoder attention | MXFP8 projection selection from the pinned source |
| MTP routed experts | NVFP4, BF16 activations; block scales stored directly |
| Vision attention linears | MXFP8 E4M3 values; UE8M0 scales per 32 weights; 54 matrices |
| Vision MLP and merger linears | NVFP4 E2M1 values; E4M3 scales per 16 weights and FP32 global scale; 56 matrices; BF16 activations |
| Other vision tensors | BF16; 223 tensors, including normalization, biases, position embeddings, and convolutions |
| Normalization parameters | 100 FP32 tensors (97 hyperconnection and 3 PLE norms); 203 BF16 tensors; original bytes preserved |
Vision uses weight-only post-training conversion for NVFP4 linears and dynamic MXFP8 attention activations. The vision weights occupy 326,652,352 bytes (311.52 MiB), saving 544.75 MiB of tensor storage versus their BF16 source. These numbers exclude runtime workspaces, activations, and KV cache.
The pinned input is local-inference-lab/Qwen3.8-Flash-Next-NVFP4-MXFP8-CSF-QAD at revision ac1c8d8edfb88a41df837e8ca431e0ec237c139d. All tensors outside the converted vision linear weights retain their source values and dtypes. CSF reconstructs the original scale bytes exactly.
Storage contract
The checkpoint contains 21 safetensors shards targeting 5 GB each, under tensors/. model.safetensors.index.json maps stored tensors to these files.
Scale encoding: weight_scale_encoding: "csf". Codec: byte-window4-fixed-stream-u24-exceptions/1. The 73,728 compressed matrices are exclusively main-decoder routed-expert E4M3 block scales. Each logical scale tensor is represented by a uint8 .nvfp4_csf_fixed stream and uint32 .nvfp4_csf_exceptions. MTP, vision, PLE, MXFP8, global, and activation scales remain uncompressed.
Runtime requirements
config.json uses the standard quant_method: "modelopt" and quant_algo: "MIXED_PRECISION". Decoder expert recipes declare quant_algo: "NVFP4", group_size: 16, and weight_scale_encoding: "csf". MTP and vision recipes retain their own precision settings without CSF encoding.
vLLM uses its standard safetensors loader and modelopt_mixed quantization. The quantization layer receives compressed scale tensors through normal weight-loading hooks and prepares TP-local scales for b12x. No checkpoint-root setting or CSF-specific load format is needed.
The checkpoint retains all trained FP32 normalization tensors. The b12x HC/PLE kernels require BF16 affine weights, so the vLLM loader converts those 100 tensors to BF16 in memory without changing the checkpoint.
Validation
Every stored tensor and shard passed SHA-256 verification. Retained tensors match the pinned input byte-for-byte. Every compressed scale passed independent lossless reconstruction, and reconstructed shard hashes match the reference serialization. Vision NVFP4 packing and rounding were checked against an independent E2M1 reference. GPU inference and multimodal quality evaluation have not been run for this checkpoint.
License
LICENSE, NOTICE, and LICENSES/ retain the source distribution's license and attribution materials, including the upstream model terms.
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