Qwen: Qwen3 VL 235B A22B Thinking
Analysis Summary
Qwen3 VL 235B A22B Thinking is a multimodal reasoning model accepting text and images, with a 131K context window, tool use, and function calling. Its mathematical and general language results are stronger than its coding profile, making it a useful specialist for visual analysis, structured interpretation, and complex asset review.
Agency workloads could include image-grounded content briefs, document and screenshot analysis, visual quality checks, multimodal research, and structured extraction from client materials. The context window supports substantial documents, while tool access enables connected workflows. It is less compelling for large-scale software engineering or fully autonomous agents, and its output pricing is higher than lightweight alternatives.
Adopt it when visual understanding is central to the task. For text-only bulk content and coding, use a cheaper or more specialised model with stronger measured performance.
Assessed August 9, 2026
Editorial notes
Qwen3 VL 235B Thinking combines vision, tool use, strong mathematical reasoning, and a 131K context window for multimodal analysis; its broader intelligence and coding results limit it as a general production model.
Rankings consider pricing, capabilities, benchmarks, and real-world applicability and are refreshed as new models launch. Feedback?
DFO Verdict
Qwen3 VL 235B Thinking combines vision, tool use, strong mathematical reasoning, and a 131K context window for multimodal analysis; its broader intelligence and coding results limit it as a general production model.
Benchmark scores
Magenta = intelligence · Ink = technical/agentic · Cyan = content & long-context · Grey = community benchmarks. Data: Artificial Analysis, Hugging Face.
20.9 Intelligence Index·88.3 Math Index
How Qwen: Qwen3 VL 235B A22B Thinking compares
Qwen: Qwen3 VL 235B A22B Thinking ranks #172 of 427 AI models we track for overall intelligence. Its 131K-token context window is larger than 50% of the models we list. At $0.40 per million input tokens it is cheaper than 42% of comparable models.
Dark bar = input · light bar = output, scaled to the priciest peer.
1M tokens ≈ 8 full-length novels or ~2,500 pages of business documents in a single request.
Strongest on business fit. The pulled-in technical corner is the trade-off, and if the shape matters more than the price, this is your model.
Compare shapes side-by-side →Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $0.40 | $0.000400 |
| Output | $4.00 | $0.004000 |
What would Qwen: Qwen3 VL 235B A22B Thinking cost your business?
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A website chatbot handling around 100 customer conversations a day, a few short messages each.
Full calculator with 714 models → Price Calculator
These numbers get smaller with the right architecture.
We route routine calls to cheap models and save Qwen: Qwen3 VL 235B A22B Thinking for the hard ones. Most clients cut their estimate by 60-80%.
Talk to our teamAbout Qwen: Qwen3 VL 235B A22B Thinking
Qwen3-VL-235B-A22B Thinking is a multimodal model that unifies strong text generation with visual understanding across images and video. The Thinking model is optimized for multimodal reasoning in STEM and math..
Frequently asked questions about Qwen: Qwen3 VL 235B A22B Thinking
How much does Qwen: Qwen3 VL 235B A22B Thinking cost?
Qwen: Qwen3 VL 235B A22B Thinking costs $0.40 per million input tokens and $4.00 per million output tokens.
What is the context window of Qwen: Qwen3 VL 235B A22B Thinking?
Qwen: Qwen3 VL 235B A22B Thinking has a context window of 131,072 tokens (131K).
What can Qwen: Qwen3 VL 235B A22B Thinking do?
Qwen: Qwen3 VL 235B A22B Thinking supports image/vision input, tool use, and function calling.
Who created Qwen: Qwen3 VL 235B A22B Thinking?
Qwen: Qwen3 VL 235B A22B Thinking is developed by Qwen and was released on September 23, 2025.