Qwen: Qwen3 VL 235B A22B Instruct
Alibaba • LLM
Qwen3-VL-235B-A22B Instruct is an open-weight multimodal model that unifies strong text generation with visual understanding across images and video. The Instruct model targets general vision-language use (VQA, document parsing, chart/table...
Specifications
Context Window
262K tokens
Input Price/1M
$0.30
Output Price/1M
$1.90
Parameters
—
Speed
50 tok/s
Latency (TTFT)
1.1s
Max Output
16K tokens
Benchmarks
Qwen: Qwen3 VL 235B A22B Instruct results on the main AI model evaluation benchmarks. Higher scores indicate better performance.
Agentic
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| Terminal-Bench Hard | 7.0 | 100.0 | — |
Coding
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| LiveCodeBench | 59.0 | 100.0 | — |
| SciCode | 36.0 | 100.0 | — |
| AA Coding Index | 16.5 | 100.0 | — |
Knowledge
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| MMLU-Pro | 82.0 | 100.0 | — |
Long Context
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA-LCR | 32.0 | 100.0 | — |
Math
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AIME 2025 | 71.0 | 100.0 | — |
| AA Math Index | 70.7 | 100.0 | — |
overall
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA Intelligence Index | 20.8 | 100.0 | — |
Reasoning
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| GPQA Diamond | 71.0 | 100.0 | — |
| IFBench | 43.0 | 100.0 | — |
| HLE | 6.0 | 100.0 | — |
Tool Use
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| Tau²-Bench | 35.0 | 100.0 | — |
Information
- Release date
- September 23, 2025
- Tool Calling
- ✅ Supported
- Vision
- ✅ Supported
- Audio
- ❌ Not supported
Full Analysis: Qwen: Qwen3 VL 235B A22B Instruct
What is Qwen: Qwen3 VL 235B A22B Instruct?
Qwen: Qwen3 VL 235B A22B Instruct is an AI model developed by Alibaba, classified as a large language model (LLM). It is a multimodal model, capable of processing text, images, and potentially other media types. As an open source model, it is available for download, customization, and on-premises deployment. With a context window of 262K tokens, it is suitable for processing long documents such as contracts, books, and complete codebases.
Pricing & Costs in 2026
Qwen: Qwen3 VL 235B A22B Instruct is usage-based, priced at $0.3/1M input tokens and $1.9/1M output tokens. For context: 1 million tokens is approximately 750,000 words, or about 10 average-length books. At this aggressive price point, it is one of the most cost-effective options on the market, ideal for high-volume applications like chatbots, bulk document analysis, and automation.
Benchmarks & Performance
Qwen: Qwen3 VL 235B A22B Instruct was evaluated on 13 different benchmarks, covering categories like Agentic, Coding, Knowledge, Long Context, Math, overall, Reasoning, Tool Use. Results show solid performance across available evaluations.
It's important to note that benchmarks measure specific aspects and don't capture the full user experience. Factors like instruction adherence, behavior in long conversations, and real-world task quality vary significantly between models and aren't always reflected in standard scores.
Recommended Use Cases
Qwen: Qwen3 VL 235B A22B Instruct is suitable for a wide range of AI applications: long document analysis (contracts, legal proceedings, codebases), automation with tool calling (API integration, databases, external systems), image and visual document analysis (OCR, diagrams, screenshots), multimodal processing combining text and images, high-volume chatbots and automated support, text generation, summarization, translation, and general assistance.
Comparison with Alternatives
In the 2026 AI model ecosystem, Qwen: Qwen3 VL 235B A22B Instruct competes directly with similarly capable models. Alibaba competes in this segment against OpenAI, Anthropic, Google, and Meta. The choice between models depends on the specific use case, budget, latency requirements, and need for features like multimodality and tool calling.
For a detailed side-by-side comparison, use our comparison tool or check the overall model ranking.
Frequently Asked Questions
What is Qwen: Qwen3 VL 235B A22B Instruct?
Qwen3-VL-235B-A22B Instruct is an open-weight multimodal model that unifies strong text generation with visual understanding across images and video. The Instruct model targets general vision-language use (VQA, document parsing, chart/table...
How much does Qwen: Qwen3 VL 235B A22B Instruct cost?
Qwen: Qwen3 VL 235B A22B Instruct costs $0.3/1M input tokens and $1.9/1M output tokens. For heavy usage (e.g., a chatbot handling 100k messages/month), costs can range from $10 to $1,000 depending on volume.
How does Qwen: Qwen3 VL 235B A22B Instruct compare with other models?
In available benchmarks, Qwen: Qwen3 VL 235B A22B Instruct scored: Terminal-Bench Hard: 7/100, LiveCodeBench: 59/100, SciCode: 36/100. See the full table above for a detailed comparison.
Is Qwen: Qwen3 VL 235B A22B Instruct open source?
Yes, Qwen: Qwen3 VL 235B A22B Instruct is an open source model. You can deploy it on-premises, customize it via fine-tuning, and maintain full control over your data. Check the official repository for the specific license.
What is Qwen: Qwen3 VL 235B A22B Instruct best for?
Qwen: Qwen3 VL 235B A22B Instruct excels at multimodal tasks including text and vision. With its large context window, it handles long documents, codebases, and extended conversations. It supports tool calling for API integrations and automation.
Last updated: June 01, 2026 • View methodology →