Author's Description
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. The series emphasizes robust perception (recognition of diverse real-world and synthetic categories), spatial understanding (2D/3D grounding), and long-form visual comprehension, with competitive results on public multimodal benchmarks for both perception and reasoning. Beyond analysis, Qwen3-VL supports agentic interaction and tool use: it can follow complex instructions over multi-image, multi-turn dialogues; align text to video timelines for precise temporal queries; and operate GUI elements for automation tasks. The models also enable visual coding workflows, turning sketches or mockups into code and assisting with UI debugging, while maintaining strong text-only performance comparable to the flagship Qwen3 language models. This makes Qwen3-VL suitable for production scenarios spanning document AI, multilingual OCR, software/UI assistance, spatial/embodied tasks, and research on vision-language agents.
Key Specifications
Supported Parameters
This model supports the following parameters:
Features
This model supports the following features:
Performance Summary
Qwen3-VL-235B-A22B Thinking consistently ranks among the fastest models and offers highly competitive pricing across various benchmarks. This multimodal model, designed for strong text generation and visual understanding, demonstrates particular strength in Instruction Following, achieving 81.6% accuracy (93rd percentile), indicating a robust ability to process and execute complex directives. Its Email Classification performance is also strong at 97.8% accuracy (51st percentile), showcasing effective contextual understanding. The model exhibits a reasonable ability to acknowledge uncertainty, with 95.2% accuracy in the Hallucinations benchmark (51st percentile). However, significant weaknesses are apparent in core cognitive areas. Performance in Coding, General Knowledge, and Ethics benchmarks is 0.0% accuracy, suggesting a complete inability to address these types of questions. Reasoning and Mathematics also show very low accuracy at 3.4% (5th percentile) and 3.1% (9th percentile) respectively, indicating substantial limitations in complex problem-solving and quantitative analysis. While optimized for multimodal reasoning in STEM and math, the benchmark results do not reflect this specialization in the tested categories. The model's strengths lie in its operational efficiency and specific classification/instruction adherence rather than broad knowledge or advanced reasoning.
Model Pricing
Current Pricing
| Feature | Price (per 1M tokens) |
|---|---|
| Prompt | $0.3 |
| Completion | $1.2 |
Price History
Available Endpoints
| Provider | Endpoint Name | Context Length | Pricing (Input) | Pricing (Output) |
|---|---|---|---|---|
|
Alibaba
|
Alibaba | qwen/qwen3-vl-235b-a22b-thinking | 131K | $0.3 / 1M tokens | $1.2 / 1M tokens |
|
Novita
|
Novita | qwen/qwen3-vl-235b-a22b-thinking | 131K | $0.3 / 1M tokens | $1.2 / 1M tokens |
|
Parasail
|
Parasail | qwen/qwen3-vl-235b-a22b-thinking | 65K | $0.3 / 1M tokens | $1.2 / 1M tokens |
|
Parasail
|
Parasail | qwen/qwen3-vl-235b-a22b-thinking | 262K | $0.3 / 1M tokens | $1.2 / 1M tokens |
|
SiliconFlow
|
SiliconFlow | qwen/qwen3-vl-235b-a22b-thinking | 262K | $0.45 / 1M tokens | $3.5 / 1M tokens |
|
Chutes
|
Chutes | qwen/qwen3-vl-235b-a22b-thinking | 262K | $0.3 / 1M tokens | $1.2 / 1M tokens |
|
Novita
|
Novita | qwen/qwen3-vl-235b-a22b-thinking | 131K | $0.784 / 1M tokens | $3.16 / 1M tokens |
Benchmark Results
| Benchmark | Category | Reasoning | Strategy | Free | Executions | Accuracy | Cost | Duration |
|---|
Other Models by qwen
|
|
Released | Params | Context |
|
Speed | Ability | Cost |
|---|---|---|---|---|---|---|---|
| Qwen: Qwen3 VL 32B Instruct | Oct 23, 2025 | 32B | 262K |
Text input
Image input
Text output
|
★★★ | ★★★★★ | $$ |
| Qwen: Qwen3 VL 8B Thinking | Oct 14, 2025 | 8B | 256K |
Text input
Image input
Text output
|
★ | ★ | $$$$$ |
| Qwen: Qwen3 VL 8B Instruct | Oct 14, 2025 | 8B | 256K |
Text input
Image input
Text output
|
★ | ★★ | $$$ |
| Qwen: Qwen3 VL 30B A3B Thinking | Oct 06, 2025 | 30B | 262K |
Text input
Image input
Text output
|
★ | ★★★ | $$$$ |
| Qwen: Qwen3 VL 30B A3B Instruct | Oct 06, 2025 | 30B | 131K |
Text input
Image input
Text output
|
— | — | $$$ |
| Qwen: Qwen3 VL 235B A22B Instruct | Sep 23, 2025 | 235B | 131K |
Text input
Image input
Text output
|
★★★ | ★★★★★ | $$$ |
| Qwen: Qwen3 Max | Sep 23, 2025 | — | 256K |
Text input
Text output
|
★★★★ | ★★★★★ | $$$$ |
| Qwen: Qwen3 Coder Plus | Sep 23, 2025 | ~480B | 128K |
Text input
Text output
|
★★★★ | ★★★★ | $$$$ |
| Qwen: Qwen3 Coder Flash | Sep 17, 2025 | — | 128K |
Text input
Text output
|
★★★★ | ★★★ | $$$ |
| Qwen: Qwen3 Next 80B A3B Thinking | Sep 11, 2025 | 80B | 262K |
Text input
Text output
|
★ | ★★★★ | $$$$$ |
| Qwen: Qwen3 Next 80B A3B Instruct | Sep 11, 2025 | 80B | 262K |
Text input
Text output
|
★★★★ | ★★★★ | $$$$ |
| Qwen: Qwen Plus 0728 | Sep 08, 2025 | ~20B | 1M |
Text input
Text output
|
★★★★★ | ★★★ | $$$ |
| Qwen: Qwen3 30B A3B Thinking 2507 | Aug 28, 2025 | 30B | 262K |
Text input
Text output
|
★★ | ★★★ | $$$$ |
| Qwen: Qwen3 Coder 30B A3B Instruct | Jul 31, 2025 | 30B | 262K |
Text input
Text output
|
★★★★ | ★★★ | $$ |
| Qwen: Qwen3 30B A3B Instruct 2507 | Jul 29, 2025 | 30B | 131K |
Text input
Text output
|
★★★★ | ★★★★ | $$$ |
| Qwen: Qwen3 235B A22B Thinking 2507 | Jul 25, 2025 | 235B | 131K |
Text input
Text output
|
★ | ★★★★ | $$$$$ |
| Qwen: Qwen3 Coder 480B A35B | Jul 22, 2025 | 480B | 1M |
Text input
Text output
|
★★ | ★★★ | $$$ |
| Qwen: Qwen3 Coder 480B A35B (exacto) | Jul 22, 2025 | 480B | 262K |
Text input
Text output
|
— | — | $$$$ |
| Qwen: Qwen3 235B A22B Instruct 2507 | Jul 21, 2025 | 235B | 262K |
Text input
Text output
|
★★ | ★★★ | $$$ |
| Qwen: Qwen3 30B A3B | Apr 28, 2025 | 30B | 40K |
Text input
Text output
|
★ | ★★★★★ | $$$$ |
| Qwen: Qwen3 8B | Apr 28, 2025 | 8B | 40K |
Text input
Text output
|
★ | ★★★ | $$$ |
| Qwen: Qwen3 14B | Apr 28, 2025 | 14B | 40K |
Text input
Text output
|
★★ | ★★★ | $$$ |
| Qwen: Qwen3 32B | Apr 28, 2025 | 32B | 40K |
Text input
Text output
|
★ | ★★★★ | $$$ |
| Qwen: Qwen3 235B A22B | Apr 28, 2025 | 235B | 40K |
Text input
Text output
|
★ | ★★★★ | $$$$ |
| Qwen: Qwen2.5 Coder 7B Instruct | Apr 15, 2025 | 7B | 32K |
Text input
Text output
|
— | — | $ |
| Qwen: Qwen2.5 VL 32B Instruct | Mar 24, 2025 | 32B | 128K |
Text input
Image input
Text output
|
★ | ★★★ | $$$ |
| Qwen: QwQ 32B | Mar 05, 2025 | 32B | 131K |
Text input
Text output
|
★ | ★★ | $$$ |
| Qwen: Qwen VL Plus | Feb 04, 2025 | — | 7K |
Text input
Image input
Text output
|
★★★★ | ★★ | $$$ |
| Qwen: Qwen VL Max | Feb 01, 2025 | — | 131K |
Text input
Image input
Text output
|
★★★ | ★★★ | $$$$ |
| Qwen: Qwen-Turbo | Feb 01, 2025 | — | 1M |
Text input
Text output
|
★★★★★ | ★★★★ | $$ |
| Qwen: Qwen2.5 VL 72B Instruct | Feb 01, 2025 | 72B | 32K |
Text input
Image input
Text output
|
★★★★ | ★★★★ | $$ |
| Qwen: Qwen-Plus | Feb 01, 2025 | — | 131K |
Text input
Text output
|
★★★★ | ★★★★ | $$$ |
| Qwen: Qwen-Max | Feb 01, 2025 | — | 32K |
Text input
Text output
|
★★★★ | ★★★★ | $$$$ |
| Qwen: QwQ 32B Preview Unavailable | Nov 27, 2024 | 32B | 32K |
Text input
Text output
|
— | ★ | $$ |
| Qwen2.5 Coder 32B Instruct | Nov 11, 2024 | ~500B | 32K |
Text input
Text output
|
★★★★★ | ★★★★★ | $ |
| Qwen: Qwen2.5 7B Instruct | Oct 15, 2024 | ~500B | 32K |
Text input
Text output
|
★ | ★★ | $ |
| Qwen2.5 72B Instruct | Sep 18, 2024 | ~500B | 32K |
Text input
Text output
|
★★★ | ★★ | $$$ |
| Qwen: Qwen2.5-VL 7B Instruct | Aug 27, 2024 | ~500B | 32K |
Text input
Image input
Text output
|
★★★★ | ★★ | $$ |
| Qwen 2 72B Instruct Unavailable | Jun 06, 2024 | ~500B | 32K |
Text input
Text output
|
★★★★ | ★★ | $$$$ |