Mistral Small (Feb '24)

Mistral AI 於 2024 年 2 月發布的小型模型，在效率和性能之間找到了良好平衡。作為 Mistral 早期的重要版本，展示了該公司在小型高效模型方面的技術實力。具備良好的多語言支援和推理能力，為後續的 Small 系列發展奠定了基礎。適合資源受限但需要可靠 AI 能力的應用場景。

Intelligence(Relatively Weak)

Speed(Relatively Fast)

Input Supported Modalities

Is Reasoning Model

32,768

Context Window

32,768

Maximum Output Tokens

Knowledge Cutoff

Go Compare

Pricing

￥1.44 /M tokens

Input

￥4.32 /M tokens

Output

￥10.8 /M tokens

Blended Price

Quick Simple Comparison

Input

Output

Devstral Small (May '25)

￥0.1

Codestral (Jan '25)

￥0.2

Devstral Small

￥0.1

Basic Parameters

Mistral Small (Feb '24)Technical Parameters

Parameter Count

22,000.0M

Context Length

32.77k tokens

Training Data Cutoff

Open Source Category

Proprietary

Multimodal Support

Text Only

Throughput

Release Date

2024-02-26

Response Speed

183.73,997 tokens/s

Benchmark Scores

Below is the performance of Mistral Small (Feb '24) in various standard benchmark tests. These tests evaluate the model's capabilities in different tasks and domains.

Intelligence Index

Large Language Model Intelligence Level

22.92

Large Language Model Intelligence Level

Coding Index

Indicator of AI model performance on coding tasks

12.27

Indicator of AI model performance on coding tasks

Math Index

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

28.43

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

41.9

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

30.2

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

4.4

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

11.1

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

13.4

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

56.2

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)

0.7

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

Output tokens/million

Output tokens/million

Output tokens/million

Output tokens/million

Output tokens/million

131k

Context Length

Gemini 2.0 Flash Lite (Preview)

Output tokens/million

Output tokens/million

Output tokens/million

8192

Context Length

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