This model is deprecated. We only continue performance benchmarking for the default 10k input token workload. Results for other workloads are historical and no longer updated.

Alibaba has launched a newer release, Qwen3.5 397B A17B. We suggest considering it instead.

Alibaba

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Open weights model

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Released September 2025

Qwen3 VL 235B A22B (Reasoning) Intelligence, Performance & Price Analysis

Name: Intelligence
Creator: Artificial Analysis
License: https://artificialanalysis.ai/docs/legal/Terms-of-Use.pdf

Try it out API Provider Benchmarks

Intelligence

13*

Artificial Analysis Intelligence Index

* Estimated

Speed

N/A

Output tokens per second

Cost

In -Out -

N/A

Cost per Intelligence Index task

Verbosity

N/A

Output tokens from Intelligence Index

Qwen3 VL 235B A22B (Reasoning) is below average in intelligence when comparing to other open weight models of similar size. The model supports text and image input, outputs text, and has a 262k tokens context window.

Qwen3 VL 235B A22B (Reasoning) scores 13 on the Artificial Analysis Intelligence Index, placing it below average among comparable models (median: 19).

Reasoning	Yes This page shows the reasoning version of this model. A non-reasoning variant may also exist.
Input modality	Supports: text and image
Output modality	Supports: text
Context window	262k ~393 A4 pages of size 12 Arial font
Total parameters	235B
Active parameters	22B Number of parameters active per token during inference
License	Apache 2.0
Model weights	Hugging Face

Metrics are compared against models of the same class:

Non-reasoning models → compared only with other non-reasoning models
Reasoning models → compared across both reasoning and non-reasoning
Open weights models → compared only with other open weights models of the same size class:

Tiny: ≤4B parameters
Small: 4B–40B parameters
Medium: 40B–150B parameters
Large: >150B parameters

Proprietary models → compared across proprietary and open weights models of the same price range, using a blended 3:1 input/output price ratio:

<$0.15 per 1M tokens
$0.15–$1 per 1M tokens
>$1 per 1M tokens

Intelligence

Artificial Analysis Intelligence Index · Higher is better

Speed

Output tokens per second · Higher is better

Cost per Task

Weighted average cost (USD) per Intelligence Index task · Lower is better

Intelligence

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index v4.3.2 incorporates 10 evaluations: AA-Briefcase v1.1, GDPval-AA v2.1, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1

No publicly available API

Estimate (independent evaluation forthcoming)

Artificial Analysis Intelligence Index v4.3.2 includes: AA-Briefcase v1.1, GDPval-AA v2.1, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

Artificial Analysis Intelligence Index by Open Weights / Proprietary

No publicly available API

Estimate (independent evaluation forthcoming)

Indicates whether the model weights are available. Models are labelled as 'Commercial Use Restricted' if commercial use is limited by conditions, and as 'Non-commercial' if the license prohibits commercial use.

Intelligence Index vs. Cost per Task

Artificial Analysis Intelligence Index · Weighted average cost (USD) per Artificial Analysis Intelligence Index task

Most attractive quadrant

Pareto line

Weighted average cost per Intelligence Index task. Each evaluation’s cost is calculated from input, cache hit, cache write, reasoning, and answer token prices, divided by task count, and weighted by its Intelligence Index weight.

Benchmarks

Evaluations

Intelligence evaluations measured independently by Artificial Analysis · Higher is better

No publicly available API

AA-Briefcase v1.1Updated

Agentic knowledge work, (Elo-500)/2000

AA-Omniscience Accuracy

Knowledge

AA-Omniscience Non-Hallucination Rate

1 - hallucination rate

AutomationBench-AA

Agentic SaaS workflows

GDPval-AA v2.1Updated

Agentic real-world work tasks, (Elo-500)/2000

Humanity's Last Exam

Reasoning & knowledge

GDP.pdf

Professional document reasoning, All-pass

Terminal-Bench 4.0

Agentic coding & terminal use

AA-LCR v1.1

Long context reasoning

SciCodeUnder review

Coding

CritPtUnder review

Physics reasoning

Terminal-Bench-Science 0.1New

Agentic scientific research workflows in a terminal

FrontierCode 1.1New

Agentic software engineering in open-source repositories

AA-AnalystAgent

Quantitative analysis on spreadsheets & documents

Harvey LAB-AA v1.1Updated

Legal agentic work, Hallucination-Gated All-Pass Rate

EnterpriseOps-Gym-AA

Agentic business operations

AA-3DNew

Agentic interactive 3D experiences, (Elo-500)/2000

ITBench-AA

Kubernetes incident root-cause analysis

MLCR-AA

Medical long context reasoning

MMMU-Pro

Visual reasoning

While model intelligence generally translates across use cases, specific evaluations may be more relevant for certain use cases.

AA-Omniscience

AA-Omniscience Index

AA-Omniscience Index (higher is better) measures knowledge reliability and hallucination. It rewards correct answers, penalizes hallucinations, and has no penalty for refusing to answer. Scores range from -100 to 100, where 0 means as many correct as incorrect answers, and negative scores mean more incorrect than correct.

No publicly available API

AA-PersonalityBenchNew

AA-PersonalityBench results are not available for Qwen3 VL 235B A22B

Openness Index

Artificial Analysis Openness Index: Score

Openness Index assesses model openness on a 0 to 100 normalized scale (higher is more open)

Intelligence Index Comparisons

Intelligence Index vs. Cost per Task

Artificial Analysis Intelligence Index · Weighted average cost (USD) per Artificial Analysis Intelligence Index task

Most attractive quadrant

Pareto line

Cost

Cost per Intelligence Index Task

Weighted average cost (USD) per Intelligence Index task · Segmented by token type · Lower is better

Cost to Run Artificial Analysis Intelligence Index

Cost (USD) to run all evaluations in the Artificial Analysis Intelligence Index

The cost to run the evaluations in the Artificial Analysis Intelligence Index, calculated using the model's input, cache hit, cache write, reasoning, and answer token prices and the number of tokens used across evaluations (excluding repeats).

Pricing: Cache Hit, Input, and Output

Price (USD per M Tokens)

Price per token for cached prompts (previously processed), typically offering a significant discount compared to regular input price, represented as USD per million tokens. The values shown here are the cache hit price; cache write and cache storage are billed separately and vary by provider — see "Cache pricing by provider" for detail.

Context Window

Context window: tokens limit · Higher is better

No publicly available API

Larger context windows are relevant to RAG (Retrieval Augmented Generation) LLM workflows which typically involve reasoning and information retrieval of large amounts of data.

Maximum number of combined input & output tokens. Output tokens commonly have a significantly lower limit (varied by model).

Model Size (Open Weights Models Only)

Model Size: Total and Active Parameters

Comparison between total model parameters and parameters active during inference (billions)

The total number of trainable weights and biases in the model, expressed in billions. These parameters are learned during training and determine the model's ability to process and generate responses.

The number of parameters actually executed during each inference forward pass, expressed in billions. For Mixture of Experts (MoE) models, a routing mechanism selects a subset of experts per token, resulting in fewer active than total parameters. Dense models use all parameters, so active equals total.

Frequently Asked Questions

Common questions about Qwen3 VL 235B A22B (Reasoning)

Qwen3 VL 235B A22B (Reasoning) was released on September 23, 2025.

Qwen3 VL 235B A22B (Reasoning) was created by Alibaba.

Qwen3 VL 235B A22B (Reasoning) scores 13 (estimated) on the Artificial Analysis Intelligence Index, placing it below average among other open weight models of similar size (median: 19).

Yes, Qwen3 VL 235B A22B (Reasoning) is a reasoning model. It uses extended thinking or chain-of-thought reasoning to work through complex problems before providing an answer.

Qwen3 VL 235B A22B (Reasoning) supports text and image input.

Qwen3 VL 235B A22B (Reasoning) supports text output.

Yes, Qwen3 VL 235B A22B (Reasoning) supports image input and can analyze, describe, and answer questions about images.

Yes, Qwen3 VL 235B A22B (Reasoning) is multimodal. It can process text and image input and generate text output.

Qwen3 VL 235B A22B (Reasoning) has a context window of 260k tokens. This determines how much text and conversation history the model can process in a single request.

Yes, Qwen3 VL 235B A22B (Reasoning) is open weights. The model weights are publicly available and can be downloaded for self-hosting.

Qwen3 VL 235B A22B (Reasoning) has 235 billion parameters (22 billion active).

Qwen3 VL 235B A22B (Reasoning) is a Mixture of Experts (MoE) model with 235 billion total parameters, but only 22 billion active parameters are used during inference.

Qwen3 VL 235B A22B (Reasoning) is released under the Apache 2.0 license. This license allows commercial use. View license

Qwen3 VL 235B A22B (Reasoning) achieves a score of 13 on the Artificial Analysis Intelligence Index. This composite benchmark evaluates models across reasoning, knowledge, mathematics, and coding.

Qwen3 VL 235B A22B (Reasoning) is an open weights model that can be self-hosted. View providers

Qwen3 VL 235B A22B (Reasoning) is an open weights model that can be downloaded and self-hosted. Compare providers

Qwen3 VL 235B A22B (Reasoning) Intelligence, Performance & Price Analysis

Model summary

Intelligence

Speed

Cost

Verbosity

Comparison Summary

Technical specifications

122 models in this class

Intelligence

Speed

Cost per Task

Intelligence

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index by Open Weights / Proprietary

Artificial Analysis Intelligence Index

Open Weights

Intelligence Index vs. Cost per Task

Cost per Intelligence Index Task

Artificial Analysis Intelligence Index

Benchmarks

Evaluations

Intelligence Evaluation Relevance

Artificial Analysis Intelligence Index

AA-Omniscience

AA-Omniscience Index

AA-Omniscience Index

AA-PersonalityBenchNew

Openness Index

Artificial Analysis Openness Index: Score

Intelligence Index Comparisons

Intelligence Index vs. Cost per Task

Cost per Intelligence Index Task

Artificial Analysis Intelligence Index

Cost

Cost per Intelligence Index Task

Cost per Intelligence Index Task

Cost to Run Artificial Analysis Intelligence Index

Cost to Run Artificial Analysis Intelligence Index

Pricing: Cache Hit, Input, and Output

Cache Hit

Context Window

Context Window

Context Window for RAG

Context Window

Model Size (Open Weights Models Only)

Model Size: Total and Active Parameters

Total Parameters

Active Parameters at Inference Time

Frequently Asked Questions

When was Qwen3 VL 235B A22B (Reasoning) released?

Who created Qwen3 VL 235B A22B (Reasoning)?

How intelligent is Qwen3 VL 235B A22B (Reasoning)?

Is Qwen3 VL 235B A22B (Reasoning) a reasoning model?

What input modalities does Qwen3 VL 235B A22B (Reasoning) support?

What output modalities does Qwen3 VL 235B A22B (Reasoning) support?

Can Qwen3 VL 235B A22B (Reasoning) process images?

Is Qwen3 VL 235B A22B (Reasoning) multimodal?

What is the context window of Qwen3 VL 235B A22B (Reasoning)?

Is Qwen3 VL 235B A22B (Reasoning) open source?

How many parameters does Qwen3 VL 235B A22B (Reasoning) have?

What are the active parameters of Qwen3 VL 235B A22B (Reasoning)?

What is the license for Qwen3 VL 235B A22B (Reasoning)?

How does Qwen3 VL 235B A22B (Reasoning) perform on benchmarks?

Is Qwen3 VL 235B A22B (Reasoning) available via API?

Where can I use Qwen3 VL 235B A22B (Reasoning)?