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Qwen Turbo
Qwen Turbo
A high-performance optimized large language model launched by Alibaba Cloud, focusing on improving inference speed and cost-effectiveness, and supporting long context windows and complex task processing
Intelligence(Strong)
Speed(Slow)
Input Supported Modalities
No
Is Reasoning Model
1,000,000
Context Window
4,096
Maximum Output Tokens
2024-12-31
Knowledge Cutoff
Pricing
￥0.3 /M tokens
Input
￥0.6 /M tokens
Output
￥1.05 /M tokens
Blended Price
Quick Simple Comparison
Qwen-Turbo
￥0.04
Qwen-Plus-Latest
￥0.11
Qwen3-235B-A22B
￥0.28
Basic Parameters
GPT-4.1 Technical Parameters
Parameter Count
Not Announced
Context Length
1.0M tokens
Training Data Cutoff
2024-12-31
Open Source Category
Proprietary
Multimodal Support
Text Only
Throughput
1,850
Release Date
2025-04-01
Response Speed
24.5 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
8670
Large Language Model Intelligence Level
Coding Index
7890
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
78.3
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
HLE
-
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
SciCode
-
The model's capability in code generation for scientific computing or specific scientific domains
HumanEval
72.1
Score achieved by the AI model on the specific HumanEval benchmark test set
Math 500 Score
64.2
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)
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