%20--%3e%3cdefs%3e%3cstyle%3e%20.st0%20{%20fill:%20%23061b40;%20}%20.st1%20{%20fill:%20%23306af1;%20}%20.st2%20{%20fill:%20%235ce5cf;%20}%20%3c/style%3e%3c/defs%3e%3cg%3e%3cpath%20class='st0'%20d='M55,10.5h9v3h-9v9h12V7.5h-12v3ZM64,19.5h-6v-3h6v3Z'/%3e%3cpolygon%20class='st0'%20points='69%2016.5%2078%2016.5%2078%2019.5%2069%2019.5%2069%2022.5%2081%2022.5%2081%2013.5%2072%2013.5%2072%2010.5%2081%2010.5%2081%207.5%2069%207.5%2069%2016.5'/%3e%3cpolygon%20class='st0'%20points='95%2010.5%2095%207.5%2083%207.5%2083%2022.5%2095%2022.5%2095%2019.5%2086%2019.5%2086%2016.5%2095%2016.5%2095%2013.5%2086%2013.5%2086%2010.5%2095%2010.5'/%3e%3cpath%20class='st0'%20d='M40,1.5v21h11.6l1.4-1.4v-7.6h0c0,0-1.4-1.5-1.4-1.5l1.4-1.4V2.9l-1.4-1.4h-11.6ZM50,19.5h-7v-6h7v6ZM50,10.5h-7v-6h7v6Z'/%3e%3c/g%3e%3cpath%20class='st1'%20d='M23.1,24L14.7,4.8l-4.9,11.2h3.8l-1.8,4H3.3L12.1,0H2C.9,0,0,.9,0,2v20c0,1.1.9,2,2,2h21.1Z'/%3e%3cpath%20class='st2'%20d='M34,0h-16.8l10.6,24h6.2c1.1,0,2-.9,2-2V2C36,.9,35.1,0,34,0ZM32.5,20h-4V4h4v16Z'/%3e%3c/svg%3e)
Gemini 2.5 Flash Preview
Gemini 2.5 Flash Preview
A thinking model specifically designed for the balance between price and performance. It is based on the upgraded Gemini 2.0 Flash, featuring enhanced reasoning capabilities, hybrid thinking control, multimodal functions (supporting text, image, video, and audio input), and an input context window of up to 1 million tokens.
Intelligence(Medium)
Speed(Fast)
Input Supported Modalities
Yes
Is Reasoning Model
1,000,000
Context Window
65,536
Maximum Output Tokens
2025-01-31
Knowledge Cutoff
Pricing
￥1.08 /M tokens
Input
￥4.32 /M tokens
Output
￥1.89 /M tokens
Blended Price
Quick Simple Comparison
Gemini 2.0 Pro Experimental (Feb '25)
Gemini 1.5 Pro (May '24)
￥2.5
Gemini 1.5 Pro (Sep '24)
￥2.5
Basic Parameters
GPT-4.1 Technical 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
2025-04-17
Response Speed
291.49,545 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
4876
Large Language Model Intelligence Level
Coding Index
3195
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
78.3
Massive Multitask Multimodal Understanding - Testing understanding of text, images, audio, and video
GPQA
59.4
Graduate Physics Questions Assessment - Testing advanced physics knowledge with diamond science-level questions
HLE
5
The model's comprehensive average score on the Hugging Face Open LLM Leaderboard
LiveCodeBench
40.6
Specific evaluation focused on assessing large language models' ability in real-world code writing and solving programming competition problems
SciCode
23.3
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
92.6
Score on the first 500 larger, more well-known mathematical benchmark tests
AIME Score
43.3
An indicator measuring an AI model's ability to solve high-difficulty mathematical competition problems (specifically AIME level)
Featured Recommended AI Models
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
GPT 4
openai
￥216
Input tokens/million
￥432
Output tokens/million
8192
Context Length
Gemini 1.5 Flash 8B
google
￥0.58
Input tokens/million
￥2.16
Output tokens/million
1M
Context Length
Gemma 3 4B Instruct
google
-
Input tokens/million
-
Output tokens/million
128k
Context Length
Gemini 2.0 Pro Experimental (Feb '25)
google
-
Input tokens/million
-
Output tokens/million
2M
Context Length
Llama 3.2 Instruct 11B (Vision)
meta
￥0.43
Input tokens/million
￥0.43
Output tokens/million
128k
Context Length