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GPT-5.5 (high)

OpenAIGPT

描述

GPT-5.5 is OpenAI's smartest model yet, designed for real work across agentic coding, computer use, knowledge work, and early scientific research. It matches GPT-5.4 per-token latency in real-world serving while reaching a much higher level of intelligence and using significantly fewer tokens to complete the same tasks. GPT-5.5 supports a 1M-token context window in the API and a 400K-token context window in Codex, with state-of-the-art results on Terminal-Bench 2.0, OSWorld-Verified, GDPval, FrontierMath, and CyberGym.

發布日期
2026-04-23
參數規模
上下文長度
1.1M
支援模態
image, pdf, text

能力雷達圖

51
general
69
coding
93
reasoning
70
science估算
80
agents
85
multimodal

Science 在缺少專門科學評測時使用推理能力代理估算。

排行榜排名

領域#排名分數來源
程式碼能力榜3
95.0
AA
通用能力榜3
89.0
AA
科學能力4
91.0
AA

基準測試分數 (LLM Stats)

Agents

GDPval-AA1135.00 / 3000自報
BrowseComp84.4%自報
Terminal-Bench 2.082.7%自報
CyberGym81.8%自報
BixBench80.5%自報
OSWorld-Verified78.7%自報
MCP Atlas75.3%自報
FrontierSWE73.0%自報
Finance Agent60.0%自報
SWE-Bench Pro58.6%自報
Toolathlon55.6%自報
OfficeQA Pro54.1%自報
Finance Agent v251.8%自報
GeneBench25.0%自報
Legal Agent Benchmark2.1%自報

Biology

GPQA93.6%自報

Communication

Tau2 Telecom98.0%自報

Finance

GDPval-MM84.9%自報

General

MMMU-Pro83.2%自報
LiveBench80.7%自報
MRCR v2 (8-needle)74.0%自報

Long Context

Graphwalks parents >128k58.5%自報
Graphwalks BFS >128k45.4%自報

Math

Humanity's Last Exam52.2%自報
FrontierMath35.4%自報

Reasoning

ARC-AGI95.0%自報
ARC-AGI v285.0%自報

AA 評測指數

Coding Index
71.6
Intelligence Index
53.1
Gpqa
0.9
Tau2
0.9
Terminalbench V2 1
0.8
Lcr
0.7
Ifbench
0.7
Terminalbench Hard
0.6
Scicode
0.6
Hle
0.4
Tau Banking
0.3

LLM Stats 分類評分

Legal
100
Finance
100
General
100
Agents
88
Reasoning
52
Communication
100
Physics
90
Biology
90
Chemistry
90
Multimodal
80
Safety
80
Search
80
Tool Calling
80
Vision
80
Spatial Reasoning
70
Code
70
Long Context
60
Math
60

定價

輸入價格$5 / 1M tokens
輸出價格$30 / 1M tokens
混合價格(3:1)$11.25 / 1M tokens
快取讀取價格$0.5 / 1M tokens

速度

Tokens/秒79.5
首Token延遲16.43s
首回答延遲16.43s

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
$5
$30

比較該模型在不同 API 供應商之間的定價。

外部連結