The NVIDIA Qwen3.6-27B NVFP4 model is the quantized version of Alibaba's Qwen3.6-27B model, which is an auto-regressive language model that uses an optimized transformer architecture. For more information, please check here. The NVIDIA Qwen3.6-27B NVFP4 model is quantized with Model Optimizer. **GOVERNING DOWNLOAD TERMS:** Use of the model is governed by the Apache 2.0 Developers looking to take off-the-shelf, pre-quantized models for deployment in AI Agent systems, chatbots, RAG systems, and other AI-powered applications.
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 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. Developers looking to take off-the-shelf, pre-quantized models for deployment in AI Agent systems, chatbots, RAG systems, and other AI-powered applications.
Qwen3.8 delivers substantial gains across coding, professional work, research, and long-horizon agentic tasks. The NVIDIA Qwen3.8-2.4T-A95B-NVFP4 model is the quantized version of Alibaba's Qwen3.8-2.4T-A95B model.For more information, please check here. The NVIDIA Qwen3.8-2.4T-A95B-NVFP4 model is quantized with Model Optimizer. 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 (Qwen3.8-2.4T-A95B) Model Card. **GOVERNING TERMS:** Use of the model is governed by the NVIDIA Open Model Agreement. **Additional Information:** Qwen3.8-2.4T-A95B
The NVIDIA Qwen3.8-27B NVFP4 model is a quantized version of Alibaba's Qwen3.8-27B model, which is an auto-regressive language model that uses an optimized transformer architecture. For more information on the model, please check here. The model is quantized with Model Optimizer. 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 (Qwen3.8-27B) Model Card from Qwen. **GOVERNING DOWNLOAD TERMS:** Use of the model is governed by the Apache 2.0
**IMPORTANT**: the NVFP4 scale factors in this checkpoint are in a new lossless compression format, but upstream vLLM support for this format has not yet landed. **You must use one of the containers provided below.** The NVIDIA Qwen3.8-Flash-Next-FP4-Local 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-FP4-Local model is quantized with Model Optimizer using quantization-aware distillation (QAD). The checkpoint occupies approximately **96 GiB on disk** and is best suited for local AI hardware. It has been validated with vLLM on the following hardware: * **NVIDIA RTX PRO 6000 Blackwell** — single GPU, with PLE (n-gram embedding table) offload. 850K tokens of FP8 KV Cache * **NVIDIA DGX Spark** — Can run with or without PLE offload. 1M tokens of FP8 KV Cache with PLE offload
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 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.
The NVIDIA Qwen3-8B FP4 model is the quantized version of Alibaba's Qwen3-8B model, which is an auto-regressive language model that uses an optimized transformer architecture. For more information, please check here. The NVIDIA Qwen3-8B FP4 model is quantized with TensorRT Model Optimizer. 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 (Qwen3-8B) Model Card. Use of this model is governed by Apache license 2.0
The NVIDIA Qwen3-Next-80B-A3B-Instruct NVFP4 model is the quantized version of Alibaba's Qwen3-Next-80B-A3B-Instruct model, which is an auto-regressive language model that uses an optimized transformer architecture. For more information, please check here. The NVIDIA Qwen3-Next-80B-A3B-Instruct NVFP4 model is quantized with TensorRT Model Optimizer. 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-Next-80B-A3B-Instruct) Model Card. Developers looking to take off-the-shelf, pre-quantized models for deployment in AI Agent systems, chatbots, RAG systems, and other AI-powered applications.
