Gemini 1.0 Pro

Gemini 1.0 Pro是一個自然語言處理（NLP）模型，專為多回合文本和代碼聊天以及代碼生成等任務而設計。它支持文本輸入和輸出，非常適合自然語言任務。該模型針對處理複雜的對話和生成代碼片段進行了優化。它提供可調整的安全設置並支持函數調用，但不支持JSON模式、JSON模式或系統指令。最新的穩定版本是gemini-1.0-pro-001，最後一次更新是在2024年2月。

Intelligence(Weak)

Speed(Slow)

Input Supported Modalities

Is Reasoning Model

32,768

Context Window

8,192

Maximum Output Tokens

2024-02-01

Knowledge Cutoff

Pricing

￥3.6 /M tokens

Input

￥10.8 /M tokens

Output

￥5.4 /M tokens

Blended Price

Quick Simple Comparison

Gemini 2.0 Pro Experimental (Feb '25)

Gemini 1.5 Pro (May '24)

￥2.5

Gemini 2.0 Flash Thinking Experimental (Dec '24)

Basic Parameters

GPT-4.1 Technical Parameters

Parameter Count

Not Announced

Context Length

32.77k tokens

Training Data Cutoff

2024-02-01

Open Source Category

Proprietary

Multimodal Support

Text Only

Throughput

120

Release Date

2023-12-06

Response Speed

0 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

2059

Large Language Model Intelligence Level

Coding Index

Indicator of AI model performance on coding tasks

1167

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

43.1

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

27.7

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

4.6

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

11.6

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

11.7

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

2.2

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

40.3

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)

0.7

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

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