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GPT 4o Mini Realtime (Dec '24)
GPT 4o Mini Realtime (Dec '24)
GPT-4o mini是OpenAI最新的经济高效的小型模型，旨在使人工智能更容易获得和负担得起。它在文本智能和多模态推理方面表现出色，优于GPT-3.5 Turbo等先前的模型。凭借128K令牌的上下文窗口以及对文本和视觉的支持，它提供了低成本的实时应用程序，如客户支持聊天机器人。它的价格为每百万输入代币15美分，每百万输出代币60美分，比其前身便宜得多。通过内置措施和提高对安全威胁的抵抗力来优先考虑安全。
Intelligence(Weak)
Speed(Slow)
Input Supported Modalities
Yes
Is Reasoning Model
128,000
Context Window
16,384
Maximum Output Tokens
2023-10-01
Knowledge Cutoff
Pricing
￥1.08 /M tokens
Input
￥4.32 /M tokens
Output
- /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
2023-10-01
Open Source Category
Proprietary
Multimodal Support
Text, Image
Throughput
92
Release Date
2024-12-17
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
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
40.2
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
87.2
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
AIME Score
-
An indicator measuring an AI model's ability to solve high-difficulty mathematical competition problems (specifically AIME level)
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