What are the hardware requirements for Qwen3 235B A22B Thinking 2507 NVFP4?

Qwen3 235B A22B Thinking 2507 NVFP4 requires approximately 139.2 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 NVFP4 and how large is it?

Qwen3 235B A22B Thinking 2507 NVFP4 is developed by nvidia, 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 NVFP4?

Qwen3 235B A22B Thinking 2507 NVFP4 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 NVFP4 by nvidia — VRAM 139.2GB, 256K context

Name: Qwen3 235B A22B Thinking 2507 NVFP4
Author: nvidia

Qwen3 235B A22B Thinking 2507 NVFP4 is an open-source language model by nvidia. Features: 235b LLM, VRAM: 139.2GB, Context: 256K, License: apache-2.0, LLM Explorer Score: 0.28.

8-bit Base model:quantized:qwen/qwen... Base model:qwen/qwen3-235b-a22... Conversational Model optimizer Modelopt Nvfp4 Nvidia Quantized Qwen3 Qwen3 moe Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/nvidia/Qwen3-235B-A22B-Thinking-2507-NVFP4

Qwen3 235B A22B Thinking 2507 NVFP4 Parameters and Internals

LLM Name	Qwen3 235B A22B Thinking 2507 NVFP4
Repository 🤗	https://huggingface.co/nvidia/Qwen3-235B-A22B-Thinking-2507-NVFP4
Base Model(s)	Qwen3 235B A22B Thinking 2507 Qwen/Qwen3-235B-A22B-Thinking-2507
Model Size	235b
Required VRAM	139.2 GB
Updated	2026-06-02
Maintainer	nvidia
Model Type	qwen3_moe
Model Files	5.0 GB: 1-of-28 5.0 GB: 2-of-28 5.0 GB: 3-of-28 5.0 GB: 4-of-28 5.0 GB: 5-of-28 5.0 GB: 6-of-28 5.0 GB: 7-of-28 5.0 GB: 8-of-28 5.0 GB: 9-of-28 5.0 GB: 10-of-28 5.0 GB: 11-of-28 5.0 GB: 12-of-28 5.0 GB: 13-of-28 5.0 GB: 14-of-28 5.0 GB: 15-of-28 5.0 GB: 16-of-28 5.0 GB: 17-of-28 5.0 GB: 18-of-28 5.0 GB: 19-of-28 5.0 GB: 20-of-28 5.0 GB: 21-of-28 5.0 GB: 22-of-28 5.0 GB: 23-of-28 5.0 GB: 24-of-28 4.9 GB: 25-of-28 5.0 GB: 26-of-28 5.0 GB: 27-of-28 4.3 GB: 28-of-28
Model Architecture	Qwen3MoeForCausalLM
License	apache-2.0
Context Length	262144
Model Max Length	262144
Transformers Version	4.56.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|im_end\|>
Vocabulary Size	151936
Errors	replace

Rank the Qwen3 235B A22B Thinking 2507 NVFP4 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

Best Alternatives to Qwen3 235B A22B Thinking 2507 NVFP4

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
Qwen3 235B A22B Thinking 2507	256K / 171.9 GB	20387	408
Vivo C V1	256K / 156.4 GB	415	2
... 235B A22B Instruct 2507 NVFP4	256K / 139.2 GB	14322	10
...n3 235B A22B Instruct 2507 FP8	256K / 236.5 GB	54126	147
...n3 235B A22B Thinking 2507 FP8	256K / 236.5 GB	46813	86
MiroThinker 1.7 Mini	256K / 61.1 GB	584	104

Note: green Score (e.g. "73.2") means that the model is better than nvidia/Qwen3-235B-A22B-Thinking-2507-NVFP4.