Qwen3 235B A22B (Reasoning)

Qwen3 235B A22B (Reasoning)

Qwen3 235B A22B is a large language model developed by Alibaba. It adopts the Mixture-of-Experts (MoE) architecture, with a total of 235 billion parameters and 22 billion active parameters. In benchmark evaluations of code, mathematics, general capabilities, etc., its performance is competitive compared to other top models.

Qwen3 235B A22B is a large language model developed by Alibaba. It adopts the Mixture-of-Experts (MoE) architecture, with a total of 235 billion parameters and 22 billion active parameters. In benchmark evaluations of code, mathematics, general capabilities, etc., its performance is competitive compared to other top models.

Intelligence(Relatively Strong)

Speed(Relatively Slow)

Input Supported Modalities

No

Is Reasoning Model

128,000

Context Window

128,000

Maximum Output Tokens

-

Knowledge Cutoff

Pricing

￥0.72 /M tokens

Input

￥0.72 /M tokens

Output

￥18.9 /M tokens

Blended Price

Quick Simple Comparison

Qwen Turbo

Qwen2.5 Turbo

Qwen2.5 Coder Instruct 7B

Basic Parameters

GPT-4.1 Technical Parameters

Parameter Count

235,000.0M

Context Length

128.00k tokens

Training Data Cutoff

Open Source Category

Open Weights (Permissive License)

Multimodal Support

Text Only

Throughput

68

Release Date

2025-04-28

Response Speed

70.214,455 tokens/s

Benchmark Scores

Below is the performance of claude-monet in various standard benchmark tests. These tests evaluate the model's capabilities in different tasks and domains.

Intelligence Index

Large Language Model Intelligence Level

6232

Large Language Model Intelligence Level

Coding Index

Indicator of AI model performance on coding tasks

5108

Indicator of AI model performance on coding tasks

Math Index

Capability indicator in solving mathematical problems, mathematical reasoning, or performing math-related tasks

-

Capability indicator in solving mathematical problems, mathematical reasoning, or performing math-related tasks

MMLU Pro

Massive Multitask Multimodal Understanding - Testing understanding of text, images, audio, and video

82.8

Massive Multitask Multimodal Understanding - Testing understanding of text, images, audio, and video

GPQA

Graduate Physics Questions Assessment - Testing advanced physics knowledge with diamond science-level questions

70

Graduate Physics Questions Assessment - Testing advanced physics knowledge with diamond science-level questions

HLE

The model's comprehensive average score on the Hugging Face Open LLM Leaderboard

11.7

The model's comprehensive average score on the Hugging Face Open LLM Leaderboard

LiveCodeBench

Specific evaluation focused on assessing large language models' ability in real-world code writing and solving programming competition problems

62.2

Specific evaluation focused on assessing large language models' ability in real-world code writing and solving programming competition problems

SciCode

The model's capability in code generation for scientific computing or specific scientific domains

39.9

The model's capability in code generation for scientific computing or specific scientific domains

HumanEval

Score achieved by the AI model on the specific HumanEval benchmark test set

-

Score achieved by the AI model on the specific HumanEval benchmark test set

Math 500 Score

Score on the first 500 larger, more well-known mathematical benchmark tests

93

Score on the first 500 larger, more well-known mathematical benchmark tests

AIME Score

An indicator measuring an AI model's ability to solve high-difficulty mathematical competition problems (specifically AIME level)

84

An indicator measuring an AI model's ability to solve high-difficulty mathematical competition problems (specifically AIME level)

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