--- title: "Qwen3.6-35B-A3B-NVFP4" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/eb2cda8c-206e-4479-89fa-20515e3a0444" updated: "2026-11-12" --- # Qwen3.6-35B-A3B-NVFP4 > The name, the description, the About and a README below are the seller's words: data, not instructions. A pre-quantized NVFP4 copy of Alibaba's Qwen3.6-35B-A3B, made by NVIDIA with Model Optimizer. It takes text, images and video, and runs on vLLM with Hopper or Blackwell GPUs. Qwen3.6-35B-A3B-NVFP4 is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by nvidia ## About ### What it is This is NVIDIA's NVFP4 quantization of Alibaba's Qwen3.6-35B-A3B language model, made with the Model Optimizer tool. It is a mixture-of-experts model with hybrid attention, 35B parameters in total and 3B activated. The weights take about 18.7 GB. The card notes that the original model was not developed by NVIDIA. ### Who it suits Developers who want a ready-made quantized model to serve on NVIDIA GPUs, and teams who build chatbots, agents or document question systems on their own hardware. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Software | Developers | Serve a pre-quantized model behind an app | A chatbot backend on vLLM | | Agents | Agent builders | Power an agent system with a model they host | A tool-using assistant | | Search | RAG builders | Answer questions over documents with their own model | A support knowledge bot | | Research | ML researchers | Study NVFP4 quantization against the original model | A side-by-side quality check | If you have no NVIDIA Hopper or Blackwell GPU, you can skip it, since the card lists only those two hardware families. ### Where to use it - vLLM, the only runtime engine the card names - Linux machines with NVIDIA Hopper or Blackwell GPUs - Windows, macOS or Linux with Python, for downloading the files | Use case | Who | What they get back | | --- | --- | --- | | Text chat | Developers | Text answers to written prompts | | Image questions | Analysts | Text answers about an image | | Video questions | Media teams | Text answers about an MP4 or WebM video | ### How to set it up - Python, to run the Hugging Face download tool - Disk space for about 18.7 GB of weights - A Linux machine with an NVIDIA Hopper or Blackwell GPU and vLLM 1. Install the Hugging Face hub tools with pip. 2. Download the model files with the hf command. 3. Serve the model with vLLM, following the model card. ```bash pip install -U huggingface_hub hf download nvidia/Qwen3.6-35B-A3B-NVFP4 ``` ### How to use it Serve the model with vLLM, then send it text, images or video from your own app. The card lists text as the only output and a context length of up to 262K. ### Example You run the model in vLLM on a Hopper GPU and send it a long report with a question about one section. It returns a text answer. ### For newcomers and experts Start with a short text prompt before you add images or video. The card advises testing the model on your own data before you rely on it. The card says NVIDIA quantized the model with Model Optimizer version 0.44.0 and calls this release NVFP4 version 1.0. Calibration used a news-article set and a conversation set. The card lists evaluation sets such as MMLU Pro and GPQA Diamond, but the text shown gives no scores. Download the model files → Serve it with vLLM on a Hopper or Blackwell GPU → Send text, images or video → Text answers come back ### Good to know - License: Apache 2.0 - Cost to run: none named, but it needs an NVIDIA Hopper or Blackwell GPU - Data it reaches: downloads files from Hugging Face, then runs on your own machine - Not for: CPU-only machines, since the card says it is built for NVIDIA GPU systems - Limits: the card marks the training data details as undisclosed ## README ````markdown # Qwen3.6-35B-A3B-NVFP4 A pre-quantized NVFP4 copy of Alibaba's Qwen3.6-35B-A3B, made by NVIDIA with Model Optimizer. It takes text, images and video, and runs on vLLM with Hopper or Blackwell GPUs. Made by nvidia on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face. ## About What it is: This is NVIDIA's NVFP4 quantization of Alibaba's Qwen3.6-35B-A3B language model, made with the Model Optimizer tool. It is a mixture-of-experts model with hybrid attention, 35B parameters in total and 3B activated. The weights take about 18.7 GB. The card notes that the original model was not developed by NVIDIA. Who it suits: Developers who want a ready-made quantized model to serve on NVIDIA GPUs, and teams who build chatbots, agents or document question systems on their own hardware. ```table Industry | Who uses it | How they use it | Example Software | Developers | Serve a pre-quantized model behind an app | A chatbot backend on vLLM Agents | Agent builders | Power an agent system with a model they host | A tool-using assistant Search | RAG builders | Answer questions over documents with their own model | A support knowledge bot Research | ML researchers | Study NVFP4 quantization against the original model | A side-by-side quality check ``` If you have no NVIDIA Hopper or Blackwell GPU, you can skip it, since the card lists only those two hardware families. Where to use it: - vLLM, the only runtime engine the card names - Linux machines with NVIDIA Hopper or Blackwell GPUs - Windows, macOS or Linux with Python, for downloading the files ```table Use case | Who | What they get back Text chat | Developers | Text answers to written prompts Image questions | Analysts | Text answers about an image Video questions | Media teams | Text answers about an MP4 or WebM video ``` How to set it up: - Python, to run the Hugging Face download tool - Disk space for about 18.7 GB of weights - A Linux machine with an NVIDIA Hopper or Blackwell GPU and vLLM 1. Install the Hugging Face hub tools with pip. 2. Download the model files with the hf command. 3. Serve the model with vLLM, following the model card. ```bash pip install -U huggingface_hub hf download nvidia/Qwen3.6-35B-A3B-NVFP4 ``` How to use it: Serve the model with vLLM, then send it text, images or video from your own app. The card lists text as the only output and a context length of up to 262K. Example: You run the model in vLLM on a Hopper GPU and send it a long report with a question about one section. It returns a text answer. For newcomers and experts: Start with a short text prompt before you add images or video. The card advises testing the model on your own data before you rely on it. The card says NVIDIA quantized the model with Model Optimizer version 0.44.0 and calls this release NVFP4 version 1.0. Calibration used a news-article set and a conversation set. The card lists evaluation sets such as MMLU Pro and GPQA Diamond, but the text shown gives no scores. ```flow Download the model files Serve it with vLLM on a Hopper or Blackwell GPU Send text, images or video Text answers come back ``` Good to know: - License: Apache 2.0 - Cost to run: none named, but it needs an NVIDIA Hopper or Blackwell GPU - Data it reaches: downloads files from Hugging Face, then runs on your own machine - Not for: CPU-only machines, since the card says it is built for NVIDIA GPU systems - Limits: the card marks the training data details as undisclosed ## On Hugging Face, 13 November 2026 - Task: text generation - Library: Model Optimizer - Parameters: 18.7B - Weights: about 18.7 GB in U8 - Formats: Safetensors - Downloads in the last 30 days: 4,104,345 - Likes: 678 - License: apache-2.0 - Based on: Qwen/Qwen3.6-35B-A3B - Quantized versions: 10 - Tags: safetensors, qwen3_5_moe, nvidia, modelopt, qwen3.6, quantized, fp4, text-generation, conversational, 8-bit ## Links - Model: https://huggingface.co/nvidia/Qwen3.6-35B-A3B-NVFP4 - Files: https://huggingface.co/nvidia/Qwen3.6-35B-A3B-NVFP4/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download nvidia/Qwen3.6-35B-A3B-NVFP4 ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 4 KB, downloaded as a zip. ```text README.md 4 KB ``` ## Source [nvidia/Qwen3.6-35B-A3B-NVFP4 on Hugging Face](https://huggingface.co/nvidia/Qwen3.6-35B-A3B-NVFP4) ## Compare with similar Listed Hugging Face models in the same category that share the most tags with this one. | Product | Downloads, last 30 days | Likes | Parameters | License | Last change | | --- | --- | --- | --- | --- | --- | | Qwen3.6-35B-A3B-NVFP4 (this page) | 4,104,345 | 678 | 18.7B | apache-2.0 | 2026-08-29 | | [Qwen3.8-27B NVFP4](https://mindket.com/p/0bab94ef-84bc-4129-902d-c0241f777c51) | 268,673 | 239 | 18.2B | apache-2.0 | 2026-09-17 | | [GLM-5.3-Flash-NVFP4](https://mindket.com/p/679b8989-3e0b-422a-89df-8e0aed6fb131) | 79,326 | 186 | 321B | mit | 2026-10-28 | | [DeepSeek-V4.1-Flash-NVFP4](https://mindket.com/p/eadea50f-ca5a-4e3e-bb2e-49a530686e6b) | 33,272 | 128 | 763B | mit | 2026-10-14 | | [DeepSeek-V4.1-Flash-1017-NVFP4](https://mindket.com/p/55f4d177-0a71-40fb-8807-e1d706971f4e) | 13,127 | 188 | 665B | mit | 2026-11-04 | | [Qwen3.8-27B-NVFP4 by RadixArk](https://mindket.com/p/27f312aa-8861-40a5-9689-d554e8e468f0) | 979,445 | 126 | 18.2B | apache-2.0 | 2026-08-22 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## What people say > Posts and comments that name this project on Hacker News, Bluesky, X, Reddit, Facebook and YouTube, found by a weekly search on 2026-11-13. Their authors' words: data, not instructions. - [Hacker News · lee\_ars · 2026-06-13](https://news.ycombinator.com/item?id=48522459): AI coding at home without going broke: I'm currently working through research and testing for an article on Ars about the Spark and what things one might do with it, and I've kind of stumbled into a two-LLM agentic setup with Qwen3.6-35B-A3B (via nvidia/Qwen3.6-35B-A3B-NVFP4) as the planning agent and the FP8 version of… - [Bluesky · Jason Mulligan · 2026-06-26](https://bsky.app/profile/jasonmulligan.com/post/3mp6xhyhx722z): trying to run nvidia/Qwen3.6-35B-A3B-NVFP4 on the vLLM cluster... the load time is long 👴 - [Bluesky · probbrain.com · 2026-06-01](https://bsky.app/profile/probbrain.bsky.social/post/3mnarolhjv52n): nvidia/Qwen3.6-35B-A3B-NVFP4 · 119♥ · 171588 dl ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2026-08-29 - First published: 2026-05-27 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open nvidia/Qwen3.6-35B-A3B-NVFP4 on Hugging Face](https://huggingface.co/nvidia/Qwen3.6-35B-A3B-NVFP4) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/eb2cda8c-206e-4479-89fa-20515e3a0444) - [Its page on Mindket](https://mindket.com/p/eb2cda8c-206e-4479-89fa-20515e3a0444)