Google DeepMind · frontier · Released 2026-09-27

Gemini 2.5 Pro Max: pricing, context window and benchmarks

Gemini 2.5 Pro Max is a frontier model from Google DeepMind. It offers a 200,000-token context window, costs $16.94 per million input tokens and $64.80 per million output tokens, and averages 84.8 across the index's benchmark suite.

frontierreasoningcodingvisionlong contextmultimodal
Input price
$16.94
per 1M tokens
Output price
$64.80
per 1M tokens
Context
200,000
tokens
Avg score
84.8
rank #48 of 600
Arena Elo
1450.2
modelled
Max output
65,536
tokens

Pricing

Gemini 2.5 Pro Max costs $16.94 per million input tokens and $64.80 per million output tokens. A blended 3:1 input-to-output mix works out to about $28.91 per million tokens. Cached input is listed at $2.10 per million tokens.

ItemPriceNotes
Input$16.94per 1M tokens
Output$64.80per 1M tokens
Cached input$2.10per 1M tokens
Blended 3:1$28.91estimate per 1M tokens
1M in + 1M out$81.74estimate

Benchmarks

Scores below are modelled estimates on a 0–100 scale. Use them to compare relative position, not as official vendor results.

BenchmarkScoreRankPercentileRelative
MMLU-Pro 86.7 42 93th
GPQA Diamond 79.8 59 90th
SWE-bench Verified 75.5 36 94th
HumanEval 87.0 88 85th
MATH-500 91.6 31 95th
AIME 2025 82.6 59 90th
LiveCodeBench 79.9 45 93th
IFEval 91.3 47 92th
TruthfulQA 85.5 57 91th
HellaSwag 92.9 24 96th
MMMU 79.7 62 90th
Arena Elo 1450.2 72 88th

What Gemini 2.5 Pro Max is good for

Gemini 2.5 Pro Max sits in the frontier tier of the index. It is aimed at work where answer quality matters more than unit cost: hard reasoning, multi-step coding, document analysis and multimodal inputs. At $16.94 per million input tokens and a 200,000-token context window, it is a premium option, so reserve it for tasks where a cheaper model measurably fails.

Strengths

  • Top-tier average benchmark score (84.8), placing it #48 of 600.
  • Large 200,000-token context window for long documents and agent traces.
  • Accepts more than text, including image input where the provider supports it.
  • Reasoning-oriented profile, useful for multi-step problems and structured analysis.
  • Coding benchmarks are a relative strength within its tier.

Trade-offs

  • Proprietary licence: you cannot download the weights or self-host the model.
  • Premium input pricing at $16.94 per million tokens.
  • Cost can climb quickly on long outputs and high-volume traffic.

How it compares

ModelProviderContextInput / 1MAvg score
GPT-5.1 Vision OpenAI 400000 $17.76 84.8
Gemini 2.5 Pro Max Google DeepMind 200000 $16.94 84.8
Gemini 3 Flash Pro Google DeepMind 400000 $17.71 84.8
o3 Max OpenAI 2000000 $17.82 84.8
GPT-4.1 Max OpenAI 400000 $17.34 84.7
Qwen3-Max Turbo Alibaba Cloud 1000000 $17.70 84.7

Browse all comparisons →

FAQ

How much does Gemini 2.5 Pro Max cost?

Gemini 2.5 Pro Max is listed at $16.94 per million input tokens and $64.80 per million output tokens. Cached input is $2.10 per million tokens. A blended 3:1 input-to-output mix is about $28.91 per million tokens.

What is the context window of Gemini 2.5 Pro Max?

Gemini 2.5 Pro Max has a context window of 200,000 tokens and can emit up to 65,536 output tokens per request in this index.

Is Gemini 2.5 Pro Max open weights?

No. Gemini 2.5 Pro Max is a proprietary model with a proprietary licence, so you cannot download the weights.

How does Gemini 2.5 Pro Max score on benchmarks?

Gemini 2.5 Pro Max averages 84.8 across the scored benchmarks in this index, ranking #48 of 600 models. Its strongest relative result is HellaSwag at 92.9.

What is Gemini 2.5 Pro Max best for?

Gemini 2.5 Pro Max sits in the frontier tier of the index. It is aimed at work where answer quality matters more than unit cost: hard reasoning, multi-step coding, document analysis and multimodal inputs. At $16.94 per million input tokens and a 200,000-token context window, it is a premium option, so reserve it for tasks where a cheaper model measurably fails.

Related