Qwen3 30B A3B (Reasoning)

Qwen3-30B-A3B is a relatively small Mixture-of-Experts (MoE) model in Alibaba Cloud's Qwen3 series, with a total of 30.5 billion parameters and 3.3 billion active parameters. This model features a hybrid thinking/non-thinking mode, supports 119 languages, and has enhanced agent capabilities. Its goal is to outperform previous models such as QwQ-32B while significantly reducing the number of active parameters.

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

￥5.4 /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

30,500.0M

Context Length

128.00k tokens

Training Data Cutoff

Open Source Category

Open Weights (Permissive License)

Multimodal Support

Text Only

Throughput

122

Release Date

2025-04-28

Response Speed

91.70,675 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

5560

Large Language Model Intelligence Level

Coding Index

Indicator of AI model performance on coding tasks

3953

Indicator of AI model performance on coding tasks

Math Index

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

77.7

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

61.6

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

6.6

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

50.6

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

28.5

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

Math 500 Score

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

95.9

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)

75.3

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

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