Gemini 2.5 Pro

GoogleGeminiProprietary

설명

A highly capable AI model from Google, designed for the agentic era. Gemini 2.5 Pro performs well on common benchmarks with enhanced reasoning, multimodal capabilities (text, image, video, audio input), and a 1M token context window.

출시일

2025-06-05

파라미터

—

컨텍스트 길이

1.0M

모달리티

audio, image, pdf, text, video

능력 레이더

general

coding

reasoning

science

agents

multimodal

랭킹

도메인	#순위	점수	소스
오디오	62	53.0	AA
코딩 랭킹	170	58.0	AA
종합 랭킹	191	56.0	AA
멀티모달 랭킹	33	54.0	LS
과학	111	66.0	AA

벤치마크 점수 (LLM Stats)

(LLM Stats (zeroeval))

Biology

GPQANYU + Cohere + Anthropic (2023)

86.4%자체 보고

Code

Aider-Polyglot

82.2%자체 보고

Aider-Polyglot Edit

72.7%자체 보고

LiveCodeBench

69.0%자체 보고

SWE-Bench Verified

67.2%자체 보고

Factuality

FACTS Grounding

87.8%자체 보고

SimpleQA

54.0%자체 보고

General

MRCR

93.0%자체 보고

Global-MMLU-Lite

89.2%자체 보고

MRCR 1M (pointwise)

82.9%자체 보고

MMMU

82.0%자체 보고

LiveCodeBench v5

75.6%자체 보고

Vibe-Eval

67.2%자체 보고

MRCR v2 (8-needle)

16.4%자체 보고

Healthcare

VideoMMMU

83.6%자체 보고

Math

AIME 2024

92.0%자체 보고

AIME 2025

88.0%자체 보고

Humanity's Last Exam

21.6%자체 보고

Multimodal

Video-MME

84.8%자체 보고

Reasoning

ARC-AGI v2

4.9%

AA 평가 지수

(Artificial Analysis)

Math Index(Artificial Analysis)

87.7

Coding Index(Artificial Analysis)

33.3

Intelligence Index(Artificial Analysis)

25.9

Math 500(OpenAI (2024), subset of Hendrycks et al. MATH (2021))

1.0

Aime(MAA (Mathematical Association of America))

0.9

Aime 25(MAA (Mathematical Association of America))

0.9

Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))

0.9

Gpqa(NYU + Cohere + Anthropic (2023))

0.8

Livecodebench(UC Berkeley + MIT + Cornell (2024))

0.8

Lcr(Artificial Analysis)

0.7

Tau2(Sierra + U Toronto + Vector Institute (2025))

0.5

Ifbench(Google Research (2023))

0.5

Scicode(UIUC + Argonne National Lab (2024))

0.4

Terminalbench V2 1

0.3

Terminalbench Hard(Stanford × Laude Institute (2026))

0.3

Hle(Center for AI Safety + Scale AI (2025))

0.2

Tau Banking

0.1

LLM Stats 카테고리 점수

(LLM Stats (zeroeval))

Language

Long Context

Multimodal

Physics

Healthcare

Biology

Chemistry

Reasoning

General

Code

Math

Frontend Development

Factuality

Vision

Spatial Reasoning

가격

입력 가격$1.25 / 1M 토큰

출력 가격$10 / 1M 토큰

혼합 가격 (3:1)$3.438 / 1M 토큰

캐시 읽기 가격$0.125 / 1M 토큰

속도

토큰/초0.0

첫 토큰 지연0.00s

첫 응답 지연0.00s

공급자 가격 순위

26개 공급자

최저가: Google최고가: OrcaRouter

공급자입력출력

1Google최저가

$0.00001

2Poe

$0.87

3Jiekou.AI

$1.125

4302.AI

$1.25

$10

5NanoGPT

$1.25

$10

6Abacus

$1.25

$10

7Perplexity Agent

$1.25

$10

8OpenRouter

$1.25

$10

9ZenMux

$1.25

$10

10Kilo Gateway

$1.25

$10

11SAP AI Core

$1.25

$10

12Helicone

$1.25

$10

13FrogBot

$1.25

$10

14AIHubMix

$1.25

$10

15Vercel AI Gateway

$1.25

$10

16LLM Gateway

$1.25

$10

17Vertex

$1.25

$10

18FastRouter

$1.25

$10

19Auriko

$1.25

$10

20NEAR AI Cloud

$1.25

$10

21Merge Gateway

$1.25

$10

22Ofox

$1.25

$10

23Modelis

$1.25

$10

24Impossibl

$1.25

$10

25Cortecs

$1.495

$9.964

26OrcaRouter

$2.5

$15

이 모델의 다양한 API 공급자 간 가격 비교.

외부 링크

LLM Stats Artificial Analysis