nvidia/Qwen3.5-122B-A10B-NVFP4

text-generation model by nvidia

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The NVIDIA Qwen3.5-122B-A10B-NVFP4 model is the quantized version of Alibaba's Qwen3.5-122B-A10B model, which is an auto-regressive language model that uses an optimized transformer architecture. For more information, please check here. The NVIDIA Qwen3.5-122B-A10B NVFP4 model is quantized with Model Optimizer. This model is ready for commercial/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 (Qwen3.5-122B-A10B) Model Card from Alibaba. Nvidia Model Optimizer: https://github.com/NVIDIA/Model-Optimizer Apache license 2.0 Global Developers looking to take off-the-shelf, pre-quantized models for deployment in AI Agent systems, chatbots, RAG systems, and other AI-powered applications. Huggingface 06/01/2026 via https://huggingface.co/nvidia/Qwen3.5-122B-A10B-NVFP4 Architecture Type: Transformers Network Architecture: Qwen3.5-122B-A10B Mixture of Experts Number of Model Parameters: 122B in total and 10B activated Input Type(s): Text, Image, Video Input Format(s): String, Red, Green, Blue (RGB), Video (MP4/WebM) Input Parameters: One-Dimensional…

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Model overview

nvidia/Qwen3.5-122B-A10B-NVFP4 is a text-generation 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
text-generation
Library
Model Optimizer
Recent downloads (30 days)
781,654
Cumulative likes
60
Hugging Face trending score
5
Reported safetensors parameters
64,580,759,280
Architecture
Qwen3_5MoeForConditionalGeneration
License
apache-2.0
Access
Not gated by Hugging Face
Created
2026-05-13T21:13:54.000Z
Last modified
2026-06-02T22:08:04.000Z

Compatibility and lineage

Language coverage was not reported.

Reported base models: Qwen/Qwen3.5-122B-A10B

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.

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Source: Hugging Face Hub. Metadata observed 2026-10-14T06:42:09.865Z. Daily imports are snapshots, not real-time monitoring.

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