GPT 4o (March 2025, Chatgpt 4o Latest)

GPT-4o（这里的'o'代表'omni'）是一款多功能的AI模型，它可以接受文本、音频、图像和视频输入，并生成文本、音频和图像输出。它在处理文本和代码时的表现与GPT-4 Turbo相当，但在非英语语言、视觉理解和音频理解方面有所提升。

Intelligence(Medium)

Speed(Relatively Fast)

Input Supported Modalities

Yes

Is Reasoning Model

128,000

Context Window

16,384

Maximum Output Tokens

Knowledge Cutoff

Pricing

￥18 /M tokens

Input

￥72 /M tokens

Output

￥54 /M tokens

Blended Price

Quick Simple Comparison

GPT-4.1

￥2

GPT-4.1 nano

￥0.1

GPT-4.1 mini

￥0.4

Basic Parameters

GPT-4.1 Technical Parameters

Parameter Count

Not Announced

Context Length

128.00k tokens

Training Data Cutoff

Open Source Category

Proprietary

Multimodal Support

Text, Image

Throughput

132

Release Date

2025-03-27

Response Speed

182.37,944 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

5025

Large Language Model Intelligence Level

Coding Index

Indicator of AI model performance on coding tasks

3956

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

80.3

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

65.5

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

42.5

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

36.6

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

89.3

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)

32.7

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

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