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DataBubble·

Model Detail

nvidia logo

Qwen3.8-Flash-Next-NVFP4

▲ 1079.9%
Provider: NVIDIACategory: multimodalPipeline: image-text-to-text
DB Score
48.2
Downloads
63K
Likes
188
Day
+1079.9%
Week
+0.0%
Month
+0.0%
Overview

Qwen3.8-Flash-Next-NVFP4 is a multimodal model with 59.8B parameters released by NVIDIA. The model is registered under the image-text-to-text pipeline tag on Hugging Face, distributed under a other license.

Technical

Qwen3.8-Flash-Next-NVFP4 ships with 59.8B parameters. Total weight footprint is approximately 119.6 GB, which is the relevant figure when planning local-inference VRAM. Distribution is governed by the other license — review the exact terms before commercial deployment.

Trending Signal

Downloads of Qwen3.8-Flash-Next-NVFP4 have moved +1079.9% over the past 24 hours. That is a slight downtrend, consistent with normal cooling as newer models compete for the same workloads. These numbers are signal, not guarantee — week-over-week download counts on Hugging Face also reflect mirror traffic, CI scrapes, and one-off benchmarking runs.

Read about databubble_score →
Use Cases

Qwen3.8-Flash-Next-NVFP4 is best fit for mixed text-and-image reasoning tasks such as document understanding. Treat this as a starting matrix rather than a benchmark verdict — the right deployment usually depends on the specific evaluation suite that mirrors your workload.

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Model Info
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Related News
arxiv10d ago

On the Design of Qwen3.8-Next Architecture: Evaluation, Efficiency, and Training Stability

arXiv:2608.30320v1 Announce Type: new Abstract: We describe the architecture and ablations of Qwen3.8-Flash-Next, a sparse mixture-of-experts model with 125B parameters, 6B activated per token, and additional 51B parameters of n-gram embedding tables held off the accelerator. On fourteen pre-trainin

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