
Qwen3-235B-A22B-Thinking-2507 API, Deployment, Pricing
Qwen/Qwen3-235B-A22B-Thinking-2507
Qwen3-235B-A22B-Thinking-2507 is a member of the Qwen3 large language model series developed by Alibaba's Qwen team, specializing in highly complex reasoning tasks. The model is built on a Mixture-of-Experts (MoE) architecture, with 235 billion total parameters and approximately 22 billion activated parameters per token, which enhances computational efficiency while maintaining powerful performance. As a dedicated 'thinking' model, it demonstrates significantly improved performance on tasks requiring human expertise, such as logical reasoning, mathematics, science, coding, and academic benchmarks, achieving state-of-the-art results among open-source thinking models. Furthermore, the model features enhanced general capabilities like instruction following, tool usage, and text generation, and it natively supports a 256K long-context understanding capability, making it ideal for scenarios that require deep reasoning and processing of long documents
Details
Model Provider
Qwen
Type
text
Sub Type
chat
Size
235B
Publish Time
Jul 28, 2025
Input Price
$
0.35
/ M Tokens
Output Price
$
1.42
/ M Tokens
Context length
262K
Tags
MoE,235B,262K
Compare with Other Models
See how this model stacks up against others.
Model FAQs: Usage, Deployment
Learn how to use, fine-tune, and deploy this model with ease.
What is the Qwen3-235B-A22B-Thinking-2507 model, and what are its core capabilities and technical specifications?
In which business scenarios does Qwen3-235B-A22B-Thinking-2507 perform well? Which industries or applications is it suitable for?
How can the performance and effectiveness of Qwen3-235B-A22B-Thinking-2507 be optimized in actual business use?
Compared with other models, when should Qwen3-235B-A22B-Thinking-2507 be selected?
What are SiliconFlow's key strengths in AI serverless deployment for Qwen3-235B-A22B-Thinking-2507?
What makes SiliconFlow the top platform for Qwen3-235B-A22B-Thinking-2507 API?