What are the hardware requirements for Qwen3 235B A22B Thinking 2507?

Qwen3 235B A22B Thinking 2507 requires approximately 171.9 GB of VRAM and supports a context window of 256K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3 235B A22B Thinking 2507 and how large is it?

Qwen3 235B A22B Thinking 2507 is developed by Qwen, a model with 235b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Qwen3 235B A22B Thinking 2507?

Qwen3 235B A22B Thinking 2507 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3 235B A22B Thinking 2507 by Qwen — VRAM 171.9GB, 256K context

Name: Qwen3 235B A22B Thinking 2507
Author: Qwen

Qwen3 235B A22B Thinking 2507 is an open-source language model by Qwen. Features: 235b LLM, VRAM: 171.9GB, Context: 256K, License: apache-2.0, LLM Explorer Score: 0.27.

Arxiv:2402.17463 Arxiv:2404.06654 Arxiv:2407.02490 Arxiv:2501.15383 Arxiv:2505.09388 Conversational Deploy:azure Endpoints compatible Eval-results Qwen3 moe Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Qwen/Qwen3-235B-A22B-Thinking-2507

Qwen3 235B A22B Thinking 2507 Parameters and Internals

LLM Name	Qwen3 235B A22B Thinking 2507
Repository 🤗	https://huggingface.co/Qwen/Qwen3-235B-A22B-Thinking-2507
Model Size	235b
Required VRAM	171.9 GB
Updated	2026-07-27
Maintainer	Qwen
Model Type	qwen3_moe
Model Files	4.0 GB: 1-of-118 4.0 GB: 2-of-118 4.0 GB: 3-of-118 4.0 GB: 4-of-118 4.0 GB: 5-of-118 4.0 GB: 6-of-118 4.0 GB: 7-of-118 4.0 GB: 8-of-118 4.0 GB: 9-of-118 4.0 GB: 10-of-118 4.0 GB: 11-of-118 4.0 GB: 12-of-118 4.0 GB: 13-of-118 4.0 GB: 14-of-118 4.0 GB: 15-of-118 4.0 GB: 16-of-118 4.0 GB: 17-of-118 4.0 GB: 18-of-118 4.0 GB: 19-of-118 4.0 GB: 20-of-118 4.0 GB: 21-of-118 4.0 GB: 22-of-118 4.0 GB: 23-of-118 3.9 GB: 24-of-118 4.0 GB: 25-of-118 4.0 GB: 26-of-118 4.0 GB: 27-of-118 4.0 GB: 28-of-118 4.0 GB: 29-of-118 4.0 GB: 30-of-118 4.0 GB: 31-of-118 4.0 GB: 32-of-118 4.0 GB: 33-of-118 4.0 GB: 34-of-118 4.0 GB: 35-of-118 4.0 GB: 36-of-118 4.0 GB: 37-of-118 4.0 GB: 38-of-118 4.0 GB: 39-of-118 4.0 GB: 40-of-118 4.0 GB: 41-of-118 4.0 GB: 42-of-118 4.0 GB: 43-of-118
Model Architecture	Qwen3MoeForCausalLM
License	apache-2.0
Context Length	262144
Model Max Length	262144
Transformers Version	4.51.0
Vocabulary Size	151936
Torch Data Type	bfloat16

Rank the Qwen3 235B A22B Thinking 2507 capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Quantized Models of the Qwen3 235B A22B Thinking 2507

Model	Likes	Downloads	VRAM
...3 235B A22B Thinking 2507 8bit	4	515	227 GB
...5B A22B Thinking 2507 3bit DWQ	6	204	103 GB
...5B A22B Thinking 2507 4bit DWQ	4	65	131 GB

Best Alternatives to Qwen3 235B A22B Thinking 2507

Best Alternatives	Context / RAM	Downloads	Likes
...en3 235B A22B Instruct 2507 1M	986K / 171.9 GB	4	1
Qwen3 235B A22B Instruct 2507	256K / 167.9 GB	28	10
Qwen3 235B A22B Thinking 2507	256K / 167.9 GB	14	3
Qwen3 235B A22B Instruct 2507	256K / 171.9 GB	59472	793
Vivo C V1	256K / 156.4 GB	415	2
... 235B A22B Thinking 2507 NVFP4	256K / 139.2 GB	22828	8
... 235B A22B Instruct 2507 NVFP4	256K / 139.2 GB	14322	10
...n3 235B A22B Instruct 2507 FP8	256K / 236.5 GB	54126	147
MiroThinker 1.7 Mini	256K / 61.1 GB	584	104
...n3 235B A22B Thinking 2507 FP8	256K / 236.5 GB	46813	86

Note: green Score (e.g. "73.2") means that the model is better than Qwen/Qwen3-235B-A22B-Thinking-2507.