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Mistral Medium
Mistral Medium
Intelligence(Relatively Weak)
Speed(Relatively Slow)
Input Supported Modalities
Yes
Is Reasoning Model
32,768
Context Window
-
Maximum Output Tokens
-
Knowledge Cutoff
Pricing
- /M tokens
Input
- /M tokens
Output
￥29.43 /M tokens
Blended Price
Quick Simple Comparison
Codestral-Mamba
Devstral
Codestral (Jan '25)
￥0.2
Basic Parameters
GPT-4.1 Technical Parameters
Parameter Count
Not Announced
Context Length
32.77k tokens
Training Data Cutoff
Open Source Category
Proprietary
Multimodal Support
Text Only
Throughput
Release Date
2023-12-11
Response Speed
71.13,969 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
2280
Large Language Model Intelligence Level
Coding Index
1088
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
49.1
Massive Multitask Multimodal Understanding - Testing understanding of text, images, audio, and video
GPQA
34.9
Graduate Physics Questions Assessment - Testing advanced physics knowledge with diamond science-level questions
HLE
3.4
The model's comprehensive average score on the Hugging Face Open LLM Leaderboard
LiveCodeBench
9.9
Specific evaluation focused on assessing large language models' ability in real-world code writing and solving programming competition problems
SciCode
11.8
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
40.5
Score on the first 500 larger, more well-known mathematical benchmark tests
AIME Score
3.7
An indicator measuring an AI model's ability to solve high-difficulty mathematical competition problems (specifically AIME level)
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