---
title: "Google: Gemini 2.5 Pro Preview 05-06 — price, capability and what beats it · Undominated.ai"
canonical: https://undominated.ai/models/google__gemini-2.5-pro-preview-05-06/
description: "Google: Gemini 2.5 Pro Preview 05-06: $1.25/M in, $10.00/M out. Independent capability scores, context-tier pricing, and the models that are both better and cheaper."
---

# Google: Gemini 2.5 Pro Preview 05-06 — price, capability and what beats it · Undominated.ai

> Google: Gemini 2.5 Pro Preview 05-06: $1.25/M in, $10.00/M out. Independent capability scores, context-tier pricing, and the models that are both better and cheaper.

[Leaderboard](/) / Google

# Gemini 2.5 Pro Preview 05-06

Google · released 2025-05-07

 $3.44 per million tokens, balanced Balanced Summarise Chat Code gen Agentic

## No independent quality score.

No benchmark we track has measured this model. That is not the same as measuring it and finding it wanting — we simply cannot rank it, so we do not.

### Every price dimension

| Input | $1.25 /M |
| --- | --- |
| Output | $10.00 /M |
| Cached input | $0.125 /M |
| Cache write | $0.375 /M |
| Reasoning | $10.00 /M |
| Web search | $0.014 /call |

**Past 200,000 tokens the price changes.** Input goes to $2.50/M (2×) and output to $15.00/M. The headline rate does not apply to a long-context workload.

**Reasoning tokens are billed separately** at $10.00/M, on top of output. On a reasoning-heavy workload this can be 40% of the bill and it does not appear in the advertised price.

### Independent scores

No independent benchmark has measured this model.

### Capability

| Context window | 1.0M |
| --- | --- |
| Max output | 66K |
| Input modes | text, image, file, audio, video |
| Tool use | yes |
| Reasoning | always on |
| Knowledge cutoff | 2025-01-31 |

### Provenance

| Price source | openrouter.ai |
| --- | --- |
| Fetched | 2026-08-24 |
| Quality data | unrated |

Gemini 2.5 Pro is Google’s state-of-the-art AI model designed for advanced reasoning, coding, mathematics, and scientific tasks. It employs “thinking” capabilities, enabling it to reason through responses with enhanced accuracy...