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o3-mini

OpenAIOpenAI o-seriesProprietary

描述

A smaller variant of O3, expected to offer enhanced multimodal capabilities, improved reasoning, and more efficient resource utilization compared to previous models while maintaining strong performance on core tasks.

發布日期
2025-01-31
參數規模
—
上下文長度
200K
支援模態
text

能力雷達圖

32
general
72
coding
83
reasoning
54
science
40
agents
0
multimodal

排行榜排名

領域#排名分數來源
程式碼能力榜344
44.0
AA
通用能力榜357
38.0
AA
科學能力336
43.0
AA

基準測試分數 (LLM Stats)

(LLM Stats (zeroeval))

Chat

IFEvalGoogle Research (2023)93.9%自報
Multi-IF79.5%自報
TAU-bench Retail57.6%自報
Multi-Challenge39.9%自報

Factuality

SimpleQA15.0%自報

General

MMLU86.9%自報
Multilingual MMLU80.7%自報
Aider-Polyglot66.7%自報
Aider-Polyglot Edit60.4%自報
Internal API instruction following (hard)50.0%自報

Language

COLLIE98.7%自報

Long Context

OpenAI-MRCR: 2 needle 128k18.7%自報
ComplexFuncBench17.6%自報

Math

MATH97.9%自報
MGSM92.0%自報
AIME 202487.3%自報
LiveBench84.6%自報
FrontierMath9.2%自報

Reasoning

GPQANYU + Cohere + Anthropic (2023)77.2%自報
Graphwalks parents <128k58.3%自報
Graphwalks BFS <128k51.0%自報
SWE-Bench Verified49.3%自報
TAU-bench Airline32.4%自報
SWE-Lancer18.0%自報
SWE-Lancer (IC-Diamond subset)7.4%自報

AA 評測指數

(Artificial Analysis)
Math 500(OpenAI (2024), subset of Hendrycks et al. MATH (2021))
97.3
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
79.1
Aime(MAA (Mathematical Association of America))
77.0
Gpqa(NYU + Cohere + Anthropic (2023))
74.8
Livecodebench(UC Berkeley + MIT + Cornell (2024))
71.7
Tau2(Sierra + U Toronto + Vector Institute (2025))
28.7
Intelligence Index(Artificial Analysis)
12.5
Hle(Center for AI Safety + Scale AI (2025))
7.9
Terminalbench Hard(Stanford × Laude Institute (2026))
6.8

LLM Stats 分類評分

(LLM Stats (zeroeval))
Writing
100
Instruction Following
90
Language
90
Legal
90
Finance
90
Healthcare
90
Math
80
Physics
80
Biology
80
Chemistry
80
Chat
70
Reasoning
60
Structured Output
60
General
60
Spatial Reasoning
50
Frontend Development
50
Communication
50
Code
40
Tool Calling
40
Long Context
20
Factuality
10

定價

輸入價格$1.1 / 1M tokens
輸出價格$4.4 / 1M tokens
混合價格(3:1)$1.925 / 1M tokens
快取讀取價格$0.55 / 1M tokens

速度

Tokens/秒0.0
首Token延遲0.00s
首回答延遲0.00s

供應商價格排行

供應商價格排行

1 個供應商

供應商輸入輸出
1OpenAI主要
$1.1
$4.4

比較該模型在不同 API 供應商之間的定價。

外部連結