--- title: "Qwen3.5-35B-A3B" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/d85fe5dc-481b-4a14-b34e-a855b147dccc" updated: "2026-11-12" --- # Qwen3.5-35B-A3B > The name, the description, the About and a README below are the seller's words: data, not instructions. A multimodal chat model that reads images and text, with 35B parameters of which 3B are active at a time. For developers who host their own large model with Transformers, vLLM or similar. Qwen3.5-35B-A3B 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 Qwen ## About ### What it is Qwen3.5-35B-A3B is a post-trained model from Qwen that takes images and text and answers in text. It uses a mixture-of-experts design with 35B parameters in total and 3B active per token. The repository holds weights and configuration files in the Hugging Face Transformers format. ### Who it suits Developers and teams who want to run a large open-weight model themselves, including one that reads images. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Software | Developers | Host their own chat and coding model | A coding helper behind an internal tool | | Research | AI researchers | Study a mixture-of-experts model with vision | Compare it with other open models | | Enterprise | Platform teams | Serve a model on their own servers | An internal assistant that reads screenshots | | Education | Language teams | Use its multilingual coverage, listed at 201 languages and dialects | A tutor that answers in several languages | You can skip it if you have no server-class GPU memory, or if you only want a hosted chat. The maker points to a hosted version for that. ### Where to use it - Hugging Face Transformers - vLLM, SGLang and KTransformers, which the card names as compatible - Windows, macOS or Linux, with Python for the download step - Alibaba Cloud Model Studio, where the hosted Qwen3.5-Flash version runs | Use case | Who | What they get back | | --- | --- | --- | | Image and text questions | Developers | Text answers about a picture you supply | | Self-hosted assistant | Platform teams | A model on your own hardware | | Long documents | Analysts | Context of 262,144 tokens, stretchable to 1,010,000 | ### How to set it up - Python and pip on your computer - Large GPU memory, since the BF16 weights are about 71.9 GB and a 4-bit copy is about 18 GB by estimate - One of the compatible runtimes the card names 1. Install the Hugging Face hub package. 2. Download the model files with the hf command. 3. Open the model card and your chosen runtime's docs to serve the model. ```sh pip install -U huggingface_hub hf download Qwen/Qwen3.5-35B-A3B ``` ### How to use it Load the files in Transformers or one of the other named runtimes, then send it an image, text or both. The card describes the repository as the post-trained model, ready for those tools. ```sh hf download Qwen/Qwen3.5-35B-A3B ``` ### Example You send a screenshot of an error dialog and ask what it means. The model reads the image and answers in text with an explanation and likely causes. ### For newcomers and experts If you are new, a model this size needs a lot of memory, so start by reading the model card and checking your hardware. If you cannot host it, the hosted Qwen3.5-Flash is the easier path. If you know the field, the card describes 40 layers laid out as repeating Gated DeltaNet and Gated Attention blocks, each followed by mixture-of-experts. There are 256 experts, with 8 routed and 1 shared active. Context is 262,144 tokens natively. The weights come from the Qwen3.5-35B-A3B-Base checkpoint. Image and text input → Vision encoder plus language model → Expert layers, 3B active parameters → Text answer Weight size in GB | Label | Value | | --- | --- | | BF16 | 71.9 GB | | 4-bit estimate | 18 GB | ### Good to know - License: Apache 2.0 - Cost to run: your own GPU hardware, or the hosted Qwen3.5-Flash on Alibaba Cloud Model Studio, whose price the card does not give - Data it reaches: the files you download and the images and text you send it - Versions: others have published 317 quantized and 202 fine-tuned copies ## README ````markdown # Qwen3.5-35B-A3B A multimodal chat model that reads images and text, with 35B parameters of which 3B are active at a time. For developers who host their own large model with Transformers, vLLM or similar. Made by Qwen 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: Qwen3.5-35B-A3B is a post-trained model from Qwen that takes images and text and answers in text. It uses a mixture-of-experts design with 35B parameters in total and 3B active per token. The repository holds weights and configuration files in the Hugging Face Transformers format. Who it suits: Developers and teams who want to run a large open-weight model themselves, including one that reads images. ```table Industry | Who uses it | How they use it | Example Software | Developers | Host their own chat and coding model | A coding helper behind an internal tool Research | AI researchers | Study a mixture-of-experts model with vision | Compare it with other open models Enterprise | Platform teams | Serve a model on their own servers | An internal assistant that reads screenshots Education | Language teams | Use its multilingual coverage, listed at 201 languages and dialects | A tutor that answers in several languages ``` You can skip it if you have no server-class GPU memory, or if you only want a hosted chat. The maker points to a hosted version for that. Where to use it: - Hugging Face Transformers - vLLM, SGLang and KTransformers, which the card names as compatible - Windows, macOS or Linux, with Python for the download step - Alibaba Cloud Model Studio, where the hosted Qwen3.5-Flash version runs ```table Use case | Who | What they get back Image and text questions | Developers | Text answers about a picture you supply Self-hosted assistant | Platform teams | A model on your own hardware Long documents | Analysts | Context of 262,144 tokens, stretchable to 1,010,000 ``` How to set it up: - Python and pip on your computer - Large GPU memory, since the BF16 weights are about 71.9 GB and a 4-bit copy is about 18 GB by estimate - One of the compatible runtimes the card names 1. Install the Hugging Face hub package. 2. Download the model files with the hf command. 3. Open the model card and your chosen runtime's docs to serve the model. ```sh pip install -U huggingface_hub hf download Qwen/Qwen3.5-35B-A3B ``` How to use it: Load the files in Transformers or one of the other named runtimes, then send it an image, text or both. The card describes the repository as the post-trained model, ready for those tools. ```sh hf download Qwen/Qwen3.5-35B-A3B ``` Example: You send a screenshot of an error dialog and ask what it means. The model reads the image and answers in text with an explanation and likely causes. For newcomers and experts: If you are new, a model this size needs a lot of memory, so start by reading the model card and checking your hardware. If you cannot host it, the hosted Qwen3.5-Flash is the easier path. If you know the field, the card describes 40 layers laid out as repeating Gated DeltaNet and Gated Attention blocks, each followed by mixture-of-experts. There are 256 experts, with 8 routed and 1 shared active. Context is 262,144 tokens natively. The weights come from the Qwen3.5-35B-A3B-Base checkpoint. ```flow Image and text input Vision encoder plus language model Expert layers, 3B active parameters Text answer ``` ```chart Title: Weight size in GB BF16: 71.9 GB 4-bit estimate: 18 GB ``` Good to know: - License: Apache 2.0 - Cost to run: your own GPU hardware, or the hosted Qwen3.5-Flash on Alibaba Cloud Model Studio, whose price the card does not give - Data it reaches: the files you download and the images and text you send it - Versions: others have published 317 quantized and 202 fine-tuned copies ## On Hugging Face, 13 November 2026 - Task: image text to text - Library: transformers - Parameters: 36B - Weights: about 71.9 GB in BF16; about 18 GB at 4-bit (estimate) - Formats: Safetensors - Downloads in the last 30 days: 1,514,731 - Likes: 1,559 - License: apache-2.0 - Based on: Qwen/Qwen3.5-35B-A3B-Base - Quantized versions: 318 - Fine-tunes: 204 - Tags: transformers, safetensors, qwen3_5_moe, image-text-to-text, conversational ## Links - Model: https://huggingface.co/Qwen/Qwen3.5-35B-A3B - Files: https://huggingface.co/Qwen/Qwen3.5-35B-A3B/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download Qwen/Qwen3.5-35B-A3B ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [Qwen/Qwen3.5-35B-A3B on Hugging Face](https://huggingface.co/Qwen/Qwen3.5-35B-A3B) ## 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 | | --- | --- | --- | --- | --- | --- | | Qwen3.5-35B-A3B (this page) | 1,514,731 | 1,559 | 36B | apache-2.0 | 2026-04-24 | | [Qwen3.6-35B-A3B](https://mindket.com/p/dfef98d7-6ad2-4a1a-9899-8ae7d54b170e) | 4,071,952 | 3,119 | 36B | apache-2.0 | 2026-11-07 | | [Qwen3.6-35B-A3B-FP8](https://mindket.com/p/ba2b931a-8b9a-43c9-9290-bc06e5a36c0a) | 3,818,590 | 448 | 36B | apache-2.0 | 2026-11-07 | | [Ornith-1.5-35B-A3B-NVFP4](https://mindket.com/p/abeb858d-fbaa-4b9f-b303-792c4e63c99b) | 1,124,337 | 73 | 19.5B | mit | 2026-08-26 | | [Qwen3.5-122B-A10B](https://mindket.com/p/91764f45-658b-46d7-99b2-1e14356f17b8) | 810,081 | 653 | 125B | apache-2.0 | 2026-04-24 | | [Qwen3.6-35B-A3B-NVFP4-Fast](https://mindket.com/p/dab11469-0f18-43a7-b023-f4a9bfcdea9c) | 695,020 | 134 | 19.8B | apache-2.0 | 2026-07-12 | 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 · andhuman · 2026-02-24](https://news.ycombinator.com/item?id=47141052): Qwen 3.5 small models out - [Bluesky · Philippe Charrière 💜 · 2026-03-15](https://bsky.app/profile/k33gorg.bsky.social/post/3mh3hh76p722o): J'ai trouvé des modèles sympas à expérimenter (pas trop mal sur un MBA M4 32GB) - huggingface.co/unsloth/Qwen... - huggingface.co/unsloth/Nemo... - [Hacker News · everlier · 2026-03-13](https://news.ycombinator.com/item?id=47369975): Show HN: A single CLI to manage llama.cpp/vLLM/Ollama models: Harbor crossed its 127th (next one is special) release. One notable added feature is ability to manage all my LLMs with a single CLI. \# list all models harbor ls \# pairs well with jq harbor ls --json \# Ollama harbor pull qwen3.5:35b \# llama.cpp harbor pull unsloth/Qwen3.5-35B-A3B-GGUF:Q8\_0 \# vllm… - [Bluesky · Hacker \& Security News · 2026-03-28](https://bsky.app/profile/hacker.at.thenote.app/post/3mi5gopckcs23): Qwen3.5-35B-A3B Uncensored Guide: Features, Capabilities, and Setup Qwen3.5-35B-A3B Uncensored is a modified version of the Qwen model that removes refusal mechanisms while retaining full functionality. It supports text and multimodal inputs, features a large context window, and … \#hackernews \#news - [Hacker News · throwaway2027 · 2026-02-27](https://news.ycombinator.com/item?id=47183027): Qwen3.5-35B-A3B - [Bluesky · AI и ML Новости · 2026-03-17](https://bsky.app/profile/ai-ru.at.thenote.app/post/3mhbzmdno7223): "Облитая" разновидность Квен, которая удаляет защитные фильтры Обзор Huihui-Qwen3.5-35B-A3B-abliterated — экспериментального "нецензурированного" варианта Qwen, созданного путем удаления фильтров безопасности посредством аблитерации. Telegram ИИ Дайджест \#ai \#news - [Hacker News · alexhans · 2026-08-05](https://news.ycombinator.com/item?id=49179706): Pi's Minimalism Is Its Advantage: You can also use PI with local models like Qwen3.5-35B-A3B 1 and they can be surprisingly good if you development in minimalistic/simple ways. One game changer when it comes to tweaking configs that are optimized for your use case is that you can easily use a "more powerful" cloud model to… - [Bluesky · Hacker \& Security News · 2026-03-17](https://bsky.app/profile/hacker.at.thenote.app/post/3mhbu6o3kwk23): The “Abliterated” Qwen Variant That Removes Safety Filters Overview of Huihui-Qwen3.5-35B-A3B-abliterated—an experimental “uncensored” Qwen variant made by removing safety filters via abliteration. \#hackernews \#news - [Hacker News · simonw · 2026-05-27](https://news.ycombinator.com/item?id=48302188): I think Anthropic and OpenAI have found product-market fit: The problem with models like Qwen 3.6 35B (which really is an excellent model) is that my expectations of what a model can do have gone SO high now. Here's a prompt I just ran against Claude Opus 4.7: \> Use python3 to experiment with whether the SQLite3 authorizer mechanism can be used to detect… - [Bluesky · woody｜AI×実用ツール専門 · 2026-03-06](https://bsky.app/profile/woody-ai-tools.bsky.social/post/3mgecmgadoz2i): VRAM16GBで稼働！画像解析も可能な Qwen3.5 登場🤖 Alibabaから最新LLM「Qwen3.5」シリーズがリリース。 - Qwen3.5-27B: VRAM\<14GBで高速動作 (34tok/s) - Qwen3.5-35B-A3B: MoE型、高性能 (37tok/s) gpt-ossの代替として注目！コンテキスト長10万対応。 ローカル環境で本格活用できるモデルが登場した。 詳細：https://pc.watch.impress.co.jp/docs/column/nishikawa/2090406.html \#AI \#テック \#LLM \#Qwen - [Hacker News · mft\_ · 2026-04-16](https://news.ycombinator.com/item?id=47793831): Qwen3.6-35B-A3B: Agentic coding power, now open to all: There was also Qwen3.5-35B-A3B in the previous generation: https://huggingface.co/Qwen/Qwen3.5-35B-A3B - [Bluesky · Awesome Agents · 2026-02-25](https://bsky.app/profile/awesomeagents.bsky.social/post/3mfotzlqlqo2n): Kimi K2.5 vs Qwen3.5-35B-A3B: Frontier Powerhouse Meets the Tiny Giant Killer https://awesomeagents.ai/tools/kimi-k2-5-vs-qwen-3-5-35b-a3b/ \#KimiK25 \#Qwen35 \#Moe ## 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: 2026-04-24 - First published: 2026-02-24 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open Qwen/Qwen3.5-35B-A3B on Hugging Face](https://huggingface.co/Qwen/Qwen3.5-35B-A3B) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/d85fe5dc-481b-4a14-b34e-a855b147dccc) - [Its page on Mindket](https://mindket.com/p/d85fe5dc-481b-4a14-b34e-a855b147dccc)