Qwen3-235B-A22B-Instruct-2507
About Qwen3-235B-A22B-Instruct-2507
Qwen3-235B-A22B-Instruct-2507 is a flagship Mixture-of-Experts (MoE) large language model from the Qwen3 series, developed by Alibaba Cloud's Qwen team. The model has a total of 235 billion parameters, with 22 billion activated per forward pass. It was released as an updated version of the Qwen3-235B-A22B non-thinking mode, featuring significant enhancements in general capabilities such as instruction following, logical reasoning, text comprehension, mathematics, science, coding, and tool usage. Additionally, the model provides substantial gains in long-tail knowledge coverage across multiple languages and shows markedly better alignment with user preferences in subjective and open-ended tasks, enabling more helpful responses and higher-quality text generation. Notably, it natively supports an extensive 256K (262,144 tokens) context window, which enhances its capabilities for long-context understanding. This version exclusively supports the non-thinking mode and does not generate <think> blocks, aiming to deliver more efficient and precise responses for tasks like direct Q&A and knowledge retrieval
Discover how Qwen3-235B-A22B-Instruct-2507's advanced reasoning, vast context window, and robust tool-use capabilities can tackle your most demanding challenges.
Ultra-Long Document Synthesis
Process and synthesize insights from massive documents, leveraging the 1M token context for legal discovery, comprehensive literature reviews, or policy analysis.
Use Case Example:
"Analyzed a 500-page legal brief and associated case law, extracting key arguments and potential precedents to draft a concise summary for a legal team, reducing research time by days."
Advanced Codebase Analysis & Refactoring
Perform deep architectural analysis, identify security vulnerabilities, and suggest refactoring across entire codebases, integrating with external static analysis tools.
Use Case Example:
"Scanned a large Python microservices repository, pinpointing cross-service data flow inefficiencies and suggesting refactoring strategies for improved scalability, integrating with a CI/CD pipeline."
Strategic Market Intelligence
Integrate and reason over diverse data sources闁炽儲鏀﹊nancial reports, market trends, news feeds闁炽儲鏁刼 infer causal relationships and generate detailed strategic recommendations.
Use Case Example:
"Synthesized quarterly earnings, social media sentiment, and competitor news to produce a multi-page market entry strategy for a new product, highlighting risks and opportunities with data-driven reasoning."
Complex Scientific Experiment Design
Analyze extensive research papers and simulation outputs to propose novel experimental parameters, validate hypotheses, and draft detailed research proposals in scientific domains.
Use Case Example:
"Assisted a materials science team by analyzing hundreds of experimental data logs and proposing optimal alloy compositions for a new high-performance material, accelerating R&D cycles."
Enterprise Knowledge & Q&A
Build intelligent systems that answer highly specific questions by synthesizing information from an entire company's documentation, internal wikis, and historical data.
Use Case Example:
"Developed an internal chatbot that answers complex HR policy questions by referencing thousands of internal documents, providing precise, context-aware responses to employees."
Metadata
Specification
State
Deprecated
Architecture
Mixture of Experts
Calibrated
Yes
Mixture of Experts
Yes
Total Parameters
235B
Activated Parameters
22B
Reasoning
No
Precision
FP8
Context length
262K
Max Tokens
262K
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