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Gemini 2.0 Flash Thinking Experimental (Dec '24)
Gemini 2.0 Flash Thinking Experimental (Dec '24)
Gemini 2.0 快速思維是一種增強的推理模型，能夠展示其思考過程以提高性能和可解釋性。結合速度與性能，Gemini 2.0 快速思維在科學和數學方面也表現出色，能夠展示其思考來解決複雜問題。
Intelligence(Relatively Weak)
Speed(Slow)
Input Supported Modalities
Yes
Is Reasoning Model
2,000,000
Context Window
65,536
Maximum Output Tokens
2024-08-01
Knowledge Cutoff
Pricing
- /M tokens
Input
- /M tokens
Output
- /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
2.0M tokens
Training Data Cutoff
2024-08-01
Open Source Category
Proprietary
Multimodal Support
Text, Image
Throughput
Release Date
2024-12-19
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
3472
Large Language Model Intelligence Level
Coding Index
-
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
GPQA
74.2
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
LiveCodeBench
-
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
HumanEval
93.9
Score achieved by the AI model on the specific HumanEval benchmark test set
Math 500 Score
48
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)
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