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Qwen: Qwen3 235B A22B Instruct 2507

Qwen3-235B-A22B-Instruct-2507 is a multilingual, instruction-tuned mixture-of-experts language model based on the Qwen3-235B architecture, with 22B active parameters per forward pass. It is optimized for general-purpose text generation, including instruction following, logical reasoning, math, code, and tool usage. The model supports a native 262K context length and does not implement "thinking mode" (<think> blocks). Compared to its base variant, this version delivers significant gains in knowledge coverage, long-context reasoning, coding benchmarks, and alignment with open-ended tasks. It is particularly strong on multilingual understanding, math reasoning (e.g., AIME, HMMT), and alignment evaluations like Arena-Hard and WritingBench.

Context Window

262K

Input Price

$0.0700/M tokens

Output Price

$0.4600/M tokens

Modality

text->text

Pricing Breakdown
Cost per million tokens for input and output
Input$0.0700/M tokens
Output$0.4600/M tokens

Cost Example: Processing 10,000 input tokens and generating 1,000 output tokens would cost approximately $0.001160

Context Window Size
Maximum tokens the model can process in a single request
Context Window262K tokens
26% of 1M max

~197K

Words Equivalent

~131

Pages of Text

~2621

Code Functions

Best Use Cases
What this model excels at
CodingProgrammingDevelopmentWritingContent-creationMathReasoningAnalysis

Related Categories:

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