by Google DeepMind

Gemini 2.5 Pro.

multimodal closed 1M ctx Transformer (MoE) Quality 80.1 Elo 1378
Cheapest input
$1.25/M
on Google AI Studio
Cheapest output
$10.0/M
on Google AI Studio
Fastest
81 tok/s
on OpenRouter
Hosted equiv.
~$3.6/hr
@ 100 tok/s on Google AI Studio
Capability snapshot

What it's best at.

Math 92.0
Coding 87.6
General knowledge 85.0
Reasoning 82.0

Scores normalised against benchmark ceilings (100 = perfect). Coloured by tier — coral 80+ frontier, lavender 65+ strong, sage 50+ solid, slate below.

Benchmarks

Published scores.

Benchmark Score Source
GPQA 64.0 official ↗
MATH 92.0 official ↗
MMLU 85.0 official ↗
MMMU 81.7 official ↗
MMLU-Pro 82.0 official ↗
HumanEval 87.6 official ↗
SWE-bench 63.8 official ↗
Leaderboard standing

Independent rankings.

LMSYS Chatbot Arena
1378
Rank #3 · Elo from blind head-to-head votes
View leaderboard ↗
Artificial Analysis Quality Index
80.0
Composite of reasoning + coding + tool-use benchmarks
View on Artificial Analysis ↗
Description

About Gemini 2.5 Pro.

Gemini 2.5 Pro is Google's frontier model — multimodal (text, image, audio, video, code) with a native 1M-token context window (2M experimentally). Trained on TPU v5p clusters. Strong on long-context retrieval (needle-in-haystack benchmarks) and competitive on reasoning benchmarks with GPT-5 and Claude Opus. Available via Google AI Studio, Vertex AI, and the consumer Gemini app. Pricing tiered by input length — first 200K tokens at the base rate, longer at 2x. Built-in code execution + grounding with Google Search for fresh-information queries.

Architecture

How it's built.

Architecture
Transformer (MoE)
Knowledge cutoff
Jan 2025
83 days from cutoff to release.
Context window

How much it can remember.

1M tokens ≈ 750,000 English words
4K 32K 128K 1M
Max output per call: 66K tokens
Capabilities

What it can do.

Vision input
Audio input
Video input
Function calling
Tool use
JSON mode
Streaming
Fine-tuning