nvidia/Qwen3.8-Flash-Next-NVFP4
image-text-to-text model by nvidia
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The NVIDIA Qwen3.8-Flash-Next NVFP4 model is the quantized version of Alibaba's Qwen3.8-Flash-Next model, which is an auto-regressive language model that uses an optimized transformer architecture. Qwen3.8-Flash-Next is a causal language model with a vision encoder, hybrid attention (Gated DeltaNet and Qwen Sparse Attention), Mixture-of-Experts, gated residual streams, and n-gram embeddings. For more information, please check here. The NVIDIA Qwen3.8-Flash-Next NVFP4 model is quantized with Model Optimizer. This model is ready for commercial or non-commercial use. This model is not owned or developed by NVIDIA. This model has been developed and built to a third-party's requirements for this application and use case; see link to Non-NVIDIA (Qwen3.8-Flash-Next) Model Card from Qwen. Governing Terms: Use of this model is governed by the NVIDIA Open Model License. ADDITIONAL INFORMATION : Qwen Community License 1.0. Qwen3.8-Flash-Next . Global Developers looking to take off-the-shelf, pre-quantized models for deployment in AI Agent systems, chatbots, RAG systems,…
Read the full model card ↗ · Preview checked 2026-11-01T09:41:57.320Z
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Model overview
nvidia/Qwen3.8-Flash-Next-NVFP4 is a image-text-to-text model repository published by nvidia on Hugging Face. The source reports the Model Optimizer library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- image-text-to-text
- Library
- Model Optimizer
- Recent downloads (30 days)
- 160,336
- Cumulative likes
- 261
- Hugging Face trending score
- 59
- Reported safetensors parameters
- 119,602,003,859
- Architecture
- Qwen4ExpForConditionalGeneration
- License
- other
- Access
- Not gated by Hugging Face
- Created
- 2026-09-02T04:03:35.000Z
- Last modified
- 2026-09-05T23:36:02.000Z
Compatibility and lineage
Language coverage was not reported.
Reported base models: Qwen/Qwen3.8-Flash-Next
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-09-18T06:35:08.044Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.