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Solstice-AI/DeepSeek-V4.1-Flash-NVFP4
DeepSeek-V4.1-Flash-NVFP4 is a image-text-to-text model from Solstice-AI. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
<div align="center" <img src="https://github.com/deepseek-ai/DeepSeek-V2/blob/main/figures/logo.svg?raw=true" width="50%" alt="DeepSeek" / <p<a href="https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash"Original Mod…
Downloads · 30 days
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.safetensors527 GB · 100%
How the weights are stored.
U8544B · 71%
From the Hugging Face model README
This is a community NVFP4 conversion of DeepSeek-V4.1-Flash, published by s-zaizen. It is not an official DeepSeek or NVIDIA release.
The original model is a multimodal Mixture-of-Experts model featuring a Causal Encoder-Decoder architecture, Compressed Sparse Attention 2, Engram conditional memory, and DSpark speculative decoding. This conversion preserves its architecture, tokenizer, vision components, and native context configuration.
| Item | Details |
|---|---|
| Source | deepseek-ai/DeepSeek-V4.1-Flash |
| Source revision | fb2764a5cf321eaa5070ca8f9e892818f477c16d |
| Backbone / Engram parameters | 552B / 196B, as reported by DeepSeek |
| Native context configuration | 1M tokens; not independently evaluated here |
| Routed expert weights | NVFP4, 16-element blocks |
| Weight files | 48 safetensors shards, 527.293 GB total |
Converted using NVIDIA Model Optimizer and its MXFP4-to-NVFP4 weight-cast routine. Activation scaling follows NVIDIA's published calibration-free input_scale1 policy: the global input scale is fixed to 1.0, and per-block E4M3 scales are dynamic at inference. These constants are not measured calibration statistics.
Only the backbone's routed experts are converted. Engram, attention, shared experts, vision, and MTP/DSpark weights retain their source formats. No calibration forward pass or model-specific inference patch is used to produce the checkpoint.
No quality or throughput benchmarks were run for this release. File integrity, tensor layouts, scale validity, and unchanged tensors were checked. These checks do not establish benchmark parity or runtime compatibility. DeepSeek's original evaluation results describe the source model, not this conversion.
The source's prompt encoding implementation is included. Use DeepSeek V4.1's encoding rather than assuming a generic Jinja chat template. See deepseek-recipe for the upstream protocol toolkit.
Download the checkpoint:
hf download s-zaizen/DeepSeek-V4.1-Flash-NVFP4 --local-dir DeepSeek-V4.1-Flash-NVFP4
Inference requires a runtime supporting DeepSeek V4.1 and mixed FP8/NVFP4 MoE checkpoints. The included upstream reference inference code is for the source format; it is not a validated NVFP4 serving recipe. No working vLLM or SGLang launch command is claimed here.
The original DeepSeek MIT license is retained for the model and accompanying source files.
DeepSeek — original model and inference code. NVIDIA — quantization tooling and numerical recipes. s-zaizen — NVFP4 conversion and publication.