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Google · Image model · GA

Gemini 3 Pro Image

Google: native image generation, optimised for speed, flexibility and contextual understanding ai.google.dev (opens in a new tab)

US$2Input / 1M
US$120Output / 1M
–Context
–AA index
–Tokens/s
–Default level

Compare with similar models Open the Model Finder

Figures checked 1 Nov 2026. A dash means not published on the sources we checked, so it stays blank rather than estimated.

Charts

List price against similar models

US$ per 1M tokens, standard tier, short prompts. Output left blank where not published.

Show the data as a table
ModelInput US$/1MOutput US$/1M
Gemini 3 Pro Image2120
Gemini 3.1 Flash Image0.560

Full sourced profile

LabGoogle
TypeImage
StatusGA ai.google.dev (opens in a new tab)
Released–
API accessYes ai.google.dev (opens in a new tab)
API model IDgemini-3-pro-image ai.google.dev (opens in a new tab)
API rate limits–
Consumer app plans–
Price at each level–
Input per 1M tokensUS$2 ai.google.dev (opens in a new tab)Image output tokens
Output per 1M tokensUS$120 ai.google.dev (opens in a new tab)Image output tokens
Cached input–
Batch in / out–
Other pricingAbout US$0.134 per 1K or 2K image, US$0.24 per 4K image ai.google.dev (opens in a new tab)
Context window–
Max output–
Input typestext, image ai.google.dev (opens in a new tab)
Output typesimage, text
WeightsClosed ai.google.dev (opens in a new tab)
Reasoning–
Tool use–
Artificial Analysis index–
Output speed–
Time to first token–
Reasoning levels–
Lab benchmark claims–
Limitations–

Tools and MCP connectors that fit

Gemini 3 Pro Image has no published tool use, so we do not match it to MCP servers. Browse AI tools

Similar alternatives

Same type, closest on quality index and blended price. A similarity, not a ranking.

Compare Gemini 3 Pro Image with GLM-Image and Grok Imagine Image

All 109 AI models · AI agents · How we check sources

Latest news from Google

All AI news

Google United States

Google DeepMind releases Gemini Robotics 2.5 for real-world robots

DeepMind says its new vision-language-action model, built with Gemini 4 Argon, was tested on more than 200 tasks, finishes tasks 20% to 30% faster than the previous version and packed automotive parts with a 96% success rate in proof-of-concept tests at Mercedes-Benz. It is rolling out through partners including Agile Robots, Apptronik and Boston Dynamics. The figures are DeepMind's own; more robot training and inference means more GPU demand in data centres.

Source: SiliconANGLE (opens in a new tab)

Google United States

One robots.txt line to opt a website out of AI training

Google says it will support a shared AI training control in robots.txt, alongside Microsoft, OpenAI and Anthropic. It is based on an IETF draft. Website owners get one switch instead of one per crawler.

Source: Google Search Central Blog (opens in a new tab)

Google United States

Google Cloud revenue more than doubles as Alphabet spends $51.4bn in a quarter

Alphabet put $51.4bn into capex in Q3, about 35% of its technical infrastructure spend going to data centres. Google Cloud revenue grew 103% to $30.7bn.

Source: Alphabet (SEC exhibit 99.1) (opens in a new tab)