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Gemini 2.5 Pro
Gemini 2.5 Pro: Google's flagship thinking model in June 2025, with an ultra-long context of 1 million tokens, native multi-modal capabilities, state-of-the-art in code and reasoning, and support for tool invocation and dynamic thinking budget.
Intelligence(Relatively Strong)
Speed(Medium)
Input Supported Modalities
Yes
Is Reasoning Model
1,000,000
Context Window
65,536
Maximum Output Tokens
2025-01-31
Knowledge Cutoff
Pricing
￥9 /M tokens
Input
￥72 /M tokens
Output
￥24.75 /M tokens
Blended Price
Quick Simple Comparison
Gemini 2.0 Flash Thinking Experimental (Dec '24)
Gemini 1.5 Pro (Sep '24)
￥2.5
Gemini 2.0 Pro Experimental (Feb '25)
Basic Parameters
Gemini 2.5 ProTechnical Parameters
Parameter Count
Not Announced
Context Length
1.0M tokens
Training Data Cutoff
2025-01-31
Open Source Category
Proprietary
Multimodal Support
Text, Image
Throughput
85
Release Date
2025-06-05
Response Speed
145.40,782 tokens/s
Benchmark Scores
Below is the performance of Gemini 2.5 Pro in various standard benchmark tests. These tests evaluate the model's capabilities in different tasks and domains.
Intelligence Index
70.49
Large Language Model Intelligence Level
Coding Index
61.46
Indicator of AI model performance on coding tasks
Math Index
92.7
Capability indicator in solving mathematical problems, mathematical reasoning, or performing math-related tasks
MMLU Pro
86.2
Massive Multitask Multimodal Understanding - Testing understanding of text, images, audio, and video
GPQA
84.4
Graduate Physics Questions Assessment - Testing advanced physics knowledge with diamond science-level questions
HLE
21.1
The model's comprehensive average score on the Hugging Face Open LLM Leaderboard
LiveCodeBench
80.1
Specific evaluation focused on assessing large language models' ability in real-world code writing and solving programming competition problems
SciCode
42.8
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
96.7
Score on the first 500 larger, more well-known mathematical benchmark tests
AIME Score
88.7
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