Qwen3 32B

Qwen3-32B is a large language model in Alibaba's Qwen3 series. It has 32.8 billion parameters, a 128k token context window, supports 119 languages, and features a hybrid thinking mode that allows switching between deep reasoning and fast response. It excels in reasoning, instruction following, and agent capabilities.

Intelligence(Medium)

Speed(Relatively Slow)

Input Supported Modalities

Is Reasoning Model

128,000

Context Window

128,000

Maximum Output Tokens

Knowledge Cutoff

Pricing

￥0.72 /M tokens

Input

￥2.16 /M tokens

Output

￥8.82 /M tokens

Blended Price

Quick Simple Comparison

Qwen2.5 Turbo

Qwen Turbo

Qwen2.5 Coder Instruct 7B

Basic Parameters

Qwen3 32BTechnical Parameters

Parameter Count

32,800.0M

Context Length

128.00k tokens

Training Data Cutoff

Open Source Category

Open Weights (Permissive License)

Multimodal Support

Text Only

Throughput

327

Release Date

2025-04-28

Response Speed

61.136,208 tokens/s

Benchmark Scores

Below is the performance of Qwen3 32B in various standard benchmark tests. These tests evaluate the model's capabilities in different tasks and domains.

Intelligence Index

Large Language Model Intelligence Level

43.52

Large Language Model Intelligence Level

Coding Index

Indicator of AI model performance on coding tasks

28.4

Indicator of AI model performance on coding tasks

Math Index

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

58.6

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

72.7

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

53.5

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

4.3

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

28.8

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

HumanEval

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

89.6

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

86.9

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)

30.3

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

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Output tokens/million

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