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GPT-5.2 (xhigh)

OpenAIGPTProprietary

描述

GPT‑5.2 introduces substantial gains in professional knowledge work, outperforming experts on GDPval with 70.9% wins or ties, and setting new highs in coding (SWE‑Bench Pro 55.6%), science (GPQA Diamond ~92–93%), math (AIME 2025: 100%), long‑context accuracy up to 256k tokens, and reliable tool‑calling (Tau2 Telecom 98.7%). It rolls out as Instant, Thinking, and Pro—faster, more structured, and less error‑prone—priced at $1.75/1M input and $14/1M output tokens, with Pro variants supporting xhigh reasoning for top‑quality, end‑to‑end execution.

發布日期
2025-12-11
參數規模
—
上下文長度
400K
支援模態
image, text

能力雷達圖

49
general
89
coding
98
reasoning
74
science
70
agents
85
multimodal

排行榜排名

領域#排名分數來源
智慧體能力模型榜68
44.0
LS
程式碼能力榜81
87.0
AA
通用能力榜52
74.0
AA
多模態榜7
71.0
LS
科學能力80
77.0
AA

基準測試分數 (LLM Stats)

(LLM Stats (zeroeval))

Agents

Toolathlon46.3%自報

Communication

Tau2 Telecom98.7%自報
Tau2 Retail82.0%自報

Language

MMMLU89.6%自報

Math

AIME 2025100.0%自報
HMMT 202599.4%自報
LiveBench74.8%
FrontierMath40.3%自報

Multimodal

VideoMMMU85.9%自報

Reasoning

Graphwalks BFS <128k94.0%自報
GPQANYU + Cohere + Anthropic (2023)92.4%自報
BrowseComp Long Context 128k92.0%自報
BrowseComp Long Context 256k89.8%自報
Graphwalks parents <128k89.0%自報
ARC-AGI86.2%自報
CharXiv-R82.1%自報
SWE-Bench Verified80.0%自報
SWE-Lancer (IC-Diamond subset)74.6%自報
BrowseCompOpenAI (2025)65.8%自報
MCP Atlas60.6%自報
ARC-AGI v252.9%自報
Humanity's Last Exam34.5%自報

Vision

ScreenSpot Pro86.3%自報
MMMU-Pro79.5%自報

AA 評測指數

(Artificial Analysis)
Math Index(Artificial Analysis)
99.0
Aime 25(MAA (Mathematical Association of America))
99.0
Gpqa(NYU + Cohere + Anthropic (2023))
90.3
Livecodebench(UC Berkeley + MIT + Cornell (2024))
88.9
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
87.4
Tau2(Sierra + U Toronto + Vector Institute (2025))
84.8
Lcr(Artificial Analysis)
82.7
Ifbench(Google Research (2023))
75.4
Terminalbench Hard(Stanford × Laude Institute (2026))
47.0
Hle(Center for AI Safety + Scale AI (2025))
37.7
Intelligence Index(Artificial Analysis)
30.4

LLM Stats 分類評分

(LLM Stats (zeroeval))
Language
90
Physics
90
Grounding
90
Healthcare
90
Biology
90
Chemistry
90
Communication
90
Multimodal
80
Reasoning
80
Search
80
Spatial Reasoning
80
Frontend Development
80
General
80
Math
70
Code
70
Tool Calling
70
Vision
70
Agents
60

定價

輸入價格$1.75 / 1M tokens
輸出價格$14 / 1M tokens
混合價格(3:1)$4.813 / 1M tokens
快取讀取價格$0.175 / 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

2 個供應商

最便宜: OpenAI最貴: Neon
供應商輸入輸出
1OpenAI最便宜
$0
$0.00001
2Neon
$1.75
$14

比較該模型在不同 API 供應商之間的定價。

外部連結