Qwen: Qwen3 235B A22B Thinking 2507
Alibaba • LLM
Qwen3-235B-A22B-Thinking-2507 is a high-performance, open-weight Mixture-of-Experts (MoE) language model optimized for complex reasoning tasks. It activates 22B of its 235B parameters per forward pass and natively supports up to 262,144...
Specifications
Context Window
131K tokens
Input Price/1M
$0.15
Output Price/1M
$1.50
Parameters
—
Max Output
262K tokens
Benchmarks
Qwen: Qwen3 235B A22B Thinking 2507 results on the main AI model evaluation benchmarks. Higher scores indicate better performance.
Coding
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| LiveCodeBench | 78.8 | 100.0 | Artificial Analysis official API |
| LiveBench Coding | 69.0 | 100.0 | Contamination-free benchmark with objective ground-truth answers |
| AA Coding Index | 23.2 | 100.0 | Artificial Analysis official API |
Data Analysis
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| LiveBench Data Analysis | 52.2 | 100.0 | Contamination-free benchmark with objective ground-truth answers |
Language
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| LiveBench Language | 69.5 | 100.0 | Contamination-free benchmark with objective ground-truth answers |
Math
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| MATH-500 | 98.4 | 100.0 | Artificial Analysis official API |
| AA Math Index | 91.0 | 100.0 | Artificial Analysis official API |
| AIME 2025 | 91.0 | 100.0 | Artificial Analysis official API |
| LiveBench Math | 73.4 | 100.0 | Contamination-free benchmark with objective ground-truth answers |
overall
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| LiveBench Global | 53.0 | 100.0 | Contamination-free benchmark with objective ground-truth answers |
| AA Intelligence Index | 29.5 | 100.0 | Artificial Analysis official API |
Reasoning
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| MMLU Pro | 84.3 | 100.0 | Artificial Analysis official API |
| GPQA Diamond | 79.0 | 100.0 | Artificial Analysis official API |
| LiveBench Reasoning | 59.4 | 100.0 | Contamination-free benchmark with objective ground-truth answers |
Information
- Tool Calling
- ✅ Supported
- Vision
- ❌ Not supported
- Audio
- ❌ Not supported
Full Analysis: Qwen: Qwen3 235B A22B Thinking 2507
What is Qwen: Qwen3 235B A22B Thinking 2507?
Qwen: Qwen3 235B A22B Thinking 2507 is an AI model developed by Alibaba, classified as a large language model (LLM). It focuses on text processing and natural language generation. As an open source model, it is available for download, customization, and on-premises deployment. With a context window of 131K tokens, it is suitable for processing long documents such as contracts, books, and complete codebases.
Pricing & Costs in 2026
Qwen: Qwen3 235B A22B Thinking 2507 is usage-based, priced at $0.1495/1M input tokens and $1.495/1M 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 235B A22B Thinking 2507 was evaluated on 14 different benchmarks, covering categories like Coding, Data Analysis, Language, Math, overall, Reasoning. Results show exceptional 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 235B A22B Thinking 2507 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), high-volume chatbots and automated support, complex reasoning, math problem solving, and logical analysis, text generation, summarization, translation, and general assistance.
Comparison with Alternatives
In the 2026 AI model ecosystem, Qwen: Qwen3 235B A22B Thinking 2507 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 235B A22B Thinking 2507?
Qwen3-235B-A22B-Thinking-2507 is a high-performance, open-weight Mixture-of-Experts (MoE) language model optimized for complex reasoning tasks. It activates 22B of its 235B parameters per forward pass and natively supports up to 262,144...
How much does Qwen: Qwen3 235B A22B Thinking 2507 cost?
Qwen: Qwen3 235B A22B Thinking 2507 costs $0.1495/1M input tokens and $1.495/1M 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 235B A22B Thinking 2507 compare with other models?
In available benchmarks, Qwen: Qwen3 235B A22B Thinking 2507 scored: LiveCodeBench: 78.8/100, LiveBench Coding: 68.97/100, AA Coding Index: 23.2/100. See the full table above for a detailed comparison.
Is Qwen: Qwen3 235B A22B Thinking 2507 open source?
Yes, Qwen: Qwen3 235B A22B Thinking 2507 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 235B A22B Thinking 2507 best for?
Qwen: Qwen3 235B A22B Thinking 2507 excels at complex reasoning and problem solving. With its large context window, it handles long documents, codebases, and extended conversations. It supports tool calling for API integrations and automation.
Last updated: May 31, 2026 • View methodology →