Qwen3.6-35B-A3B-NVFP4

Model Overview Description: The NVIDIA Qwen3.6-35B-A3B-NVFP4 model is the quantized version of Alibaba's Qwen3.6-35B-A3B model, which is an auto-regressive language model that uses an optimized transformer architecture. For more information, please check here. The NVIDIA Qwen3.6-35B-A3B-NVFP4 model is quantized with Model Optimizer. This model is ready for commercial/non-commercial use. Third-Party Community Consideration 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 (Qwen3.6-35B-A3B) Model Card from Alibaba. References NVIDIA Model Optimizer: https://github.com/NVIDIA/Model-Optimizer License/Terms of Use: Apache license 2.0 Deployment Geography: Global Use Case: Developers looking to take off-the-shelf, pre-quantized models for deployment in AI Agent systems, chatbots, RAG systems, and other AI-powered applications. Release Date: Hugging Face on 05/28/2026 via https://huggingface.co/nvidia/Qwen3.6-35B-A3B-NVFP4 Model Architecture: Architecture Type:** Transformers Network Architecture:** Mixture-of-Experts (MoE) with Hybrid Attention Number of Model Parameters:** 35B in total and 3B activated Input: Input Type(s):** Text, Image, Video Input Format(s):** String, Red, Green, Blue (RGB), Video (MP4/WebM) Input Parameters:** One-Dimensional (1D), Two-Dimensional (2D), Three-Dimensional (3D) Other Properties Related to Input:** Context length up to 262K Output: Output Type(s):** Text Output Format:** String Output Parameters:** One-Dimensional(1D): Sequences Other Properties Related to Output:** None Our AI models are designed and/or optimized to run on NVIDIA GPU-accelerated systems. By leveraging NVIDIA’s hardware (e.g. GPU cores) and software frameworks (e.g., CUDA libraries), the model achieves faster training and inference times compared to CPU-only solutions. Software Integration: Supported Runtime Engine(s):** vLLM Supported Hardware