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Magistral Medium
Medium-scale model from the Magistral series, seeking balance between performance and efficiency. Designed to provide stable and reliable AI services with good general language understanding and generation capabilities. Suitable for moderate complexity enterprise applications, handles daily text analysis, content generation, and customer service tasks, offering excellent cost-performance AI solutions for businesses.
Intelligence(Medium)
Speed(Medium)
Input Supported Modalities
Yes
Is Reasoning Model
128,000
Context Window
128,000
Maximum Output Tokens
2025-06-01
Knowledge Cutoff
Pricing
- /M tokens
Input
- /M tokens
Output
￥19.8 /M tokens
Blended Price
Quick Simple Comparison
Devstral
￥0.1
Devstral Medium
￥0.4
Devstral Small (May '25)
￥0.1
Basic Parameters
Magistral MediumTechnical Parameters
Parameter Count
24,000.0M
Context Length
128.00k tokens
Training Data Cutoff
2025-06-01
Open Source Category
Proprietary
Multimodal Support
Text, Image
Throughput
Release Date
2025-06-10
Response Speed
129.7,688 tokens/s
Benchmark Scores
Below is the performance of Magistral Medium in various standard benchmark tests. These tests evaluate the model's capabilities in different tasks and domains.
Intelligence Index
55.97
Large Language Model Intelligence Level
Coding Index
41.19
Indicator of AI model performance on coding tasks
Math Index
80.87
Capability indicator in solving mathematical problems, mathematical reasoning, or performing math-related tasks
MMLU Pro
75.3
Massive Multitask Multimodal Understanding - Testing understanding of text, images, audio, and video
GPQA
67.9
Graduate Physics Questions Assessment - Testing advanced physics knowledge with diamond science-level questions
HLE
9.5
The model's comprehensive average score on the Hugging Face Open LLM Leaderboard
LiveCodeBench
52.7
Specific evaluation focused on assessing large language models' ability in real-world code writing and solving programming competition problems
SciCode
29.7
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
91.7
Score on the first 500 larger, more well-known mathematical benchmark tests
AIME Score
70
An indicator measuring an AI model's ability to solve high-difficulty mathematical competition problems (specifically AIME level)
GPT 5 Mini
openai
￥1.8
Input tokens/million
￥14.4
Output tokens/million
400k
Context Length
GPT 5 Standard
openai
￥63
Input tokens/million
￥504
Output tokens/million
400k
Context Length
GPT 5 Nano
openai
￥0.36
Input tokens/million
￥2.88
Output tokens/million
400k
Context Length
GPT 5
openai
￥9
Input tokens/million
￥72
Output tokens/million
400k
Context Length
GLM 4.5
chatglm
￥0.43
Input tokens/million
￥1.01
Output tokens/million
131k
Context Length
Gemini 2.0 Flash Lite (Preview)
google
￥0.58
Input tokens/million
￥2.16
Output tokens/million
1M
Context Length
Gemini 1.0 Pro
google
￥3.6
Input tokens/million
￥10.8
Output tokens/million
33k
Context Length
Qwen2.5 Coder Instruct 32B
alibaba
￥0.65
Input tokens/million
￥0.65
Output tokens/million
131k
Context Length