Gemini Pro
Our best model for general performance across a wide range of tasks
Natively multimodal, with an updated long context window of up to two million tokens — the longest of any large-scale foundation model.
Demo
Longer context
1.5 Pro introduces a breakthrough context window of up to two million tokens — the longest context window of any large scale foundation model yet. It achieves near-perfect recall on long-context retrieval tasks across modalities, unlocking the ability to accurately process large-scale documents, thousands of lines of code, hours of audio, video, and more.
Better understanding across modalities
Gemini 1.5 Pro can perform highly sophisticated reasoning tasks using text, images, audio, and video. Here, it uses a hand-drawn picture to pinpoint a scene in a Buster Keaton movie.
Reasoning about vast amounts of information
Watch Gemini 1.5 Pro analyze and summarize the 402-page transcript from Apollo 11’s mission to the moon.
Pros on Pro
Developers have been putting 1.5 Pro to the test using Google AI Studio and Vertex AI.
Relentless innovation
Our research team is continually exploring new ideas at the frontier of AI, building innovative products that show consistent progress on a range of benchmarks.
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Capability |
Benchmark |
Description |
Gemini 1.5 Flash-8B (Oct 2024) |
Gemini 1.5 Flash (May 2024) |
Gemini 1.5 Flash (Sep 2024) |
Gemini 1.5 Pro (May 2024) |
Gemini 1.5 Pro (Sep 2024) |
|---|---|---|---|---|---|---|---|
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General MMLU-Pro Enhanced version of popular MMLU dataset with questions across multiple subjects with higher difficulty tasks |
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General |
MMLU-Pro |
Enhanced version of popular MMLU dataset with questions across multiple subjects with higher difficulty tasks |
Gemini 1.5 Flash-8B (Oct 2024) 58.7% |
Gemini 1.5 Flash (May 2024) 59.1% |
Gemini 1.5 Flash (Sep 2024) 67.3% |
Gemini 1.5 Pro (May 2024) 69.0% |
Gemini 1.5 Pro (Sept 2024) 75.8% |
|
Code Natural2Code Code generation across Python, Java, C++, JS, Go . Held out dataset HumanEval-like, not leaked on the web |
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Code |
Natural2Code |
Code generation across Python, Java, C++, JS, Go . Held out dataset HumanEval-like, not leaked on the web |
Gemini 1.5 Flash-8B (Oct 2024) 75.5% |
Gemini 1.5 Flash (May 2024) 77.2% |
Gemini 1.5 Flash (Sep 2024) 79.8% |
Gemini 1.5 Pro (May 2024) 82.6% |
Gemini 1.5 Pro (Sep 2024) 85.4% |
|
Math MATH Challenging math problems (incl. algebra, geometry, pre-calculus, and others) |
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Math |
MATH |
Challenging math problems (incl. algebra, geometry, pre-calculus, and others) |
Gemini 1.5 Flash-8B (Oct 2024) 58.7% |
Gemini 1.5 Flash (May 2024) 54.9% |
Gemini 1.5 Flash (Sep 2024) 77.9% |
Gemini 1.5 Pro (May 2024) 67.7% |
Gemini 1.5 Pro (Sep 2024) 86.5% |
|
HiddenMath Competition-level math problems, Held out dataset AIME/AMC-like, crafted by experts and not leaked on the web |
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HiddenMath |
Competition-level math problems, Held out dataset AIME/AMC-like, crafted by experts and not leaked on the web |
Gemini 1.5 Flash-8B (Oct 2024) 32.8% |
Gemini 1.5 Flash (May 2024) 20.3% |
Gemini 1.5 Flash (Sep 2024) 47.2% |
Gemini 1.5 Pro (May 2024) 28.0% |
Gemini 1.5 Pro (Sep 2024) 52.0% |
|
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Reasoning GPQA (diamond) Challenging dataset of questions written by domain experts in biology, physics, and chemistry |
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Reasoning |
GPQA (diamond) |
Challenging dataset of questions written by domain experts in biology, physics, and chemistry |
Gemini 1.5 Flash-8B (Oct 2024) 38.4% |
Gemini 1.5 Flash (May 2024) 41.4% |
Gemini 1.5 Flash (Sep 2024) 51.0% |
Gemini 1.5 Pro (May 2024) 46.0% |
Gemini 1.5 Pro (Sep 2024) 59.1% |
|
Multilingual WMT23 Language translation |
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|
Multilingual |
WMT23 |
Language translation |
Gemini 1.5 Flash-8B (Oct 2024) 72.6 |
Gemini 1.5 Flash (May 2024) 74.1 |
Gemini 1.5 Flash (Sep 2024) 73.9 |
Gemini 1.5 Pro (May 2024) 75.3 |
Gemini 1.5 Pro (Sep 2024) 75.1 |
|
Long Context MRCR (1M) Diagnostic long-context understanding evaluation |
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|
Long Context |
MRCR (1M) |
Diagnostic long-context understanding evaluation |
Gemini 1.5 Flash-8B (Oct 2024) 54.7% |
Gemini 1.5 Flash (May 2024) 70.1% |
Gemini 1.5 Flash (Sep 2024) 71.9% |
Gemini 1.5 Pro (May 2024) 70.5% |
Gemini 1.5 Pro (Sep 2024) 82.6% |
|
Image MMMU Multi-discipline college-level multimodal reasoning problems |
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Image |
MMMU |
Multi-discipline college-level multimodal understanding and reasoning problems |
Gemini 1.5 Flash-8B (Oct 2024) 53.7% |
Gemini 1.5 Flash (May 2024) 56.1% |
Gemini 1.5 Flash (Sep 2024) 62.3% |
Gemini 1.5 Pro (May 2024) 62.2% |
Gemini 1.5 Pro (Sep 2024) 65.9% |
|
Vibe-Eval (Reka) Visual understanding in chat models with challenging everyday examples. Evaluated with a Gemini Flash model as a rater |
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Vibe-Eval (Reka) |
Visual understanding in chat models with challenging everyday examples. Evaluated with a Gemini Flash model as a rater |
Gemini 1.5 Flash-8B (Oct 2024) 40.9% |
Gemini 1.5 Flash (May 2024) 44.8% |
Gemini 1.5 Flash (Sep 2024) 48.9% |
Gemini 1.5 Pro (May 2024) 48.9% |
Gemini 1.5 Pro (Sep 2024) 53.9% |
|
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MathVista Mathematical reasoning in visual contexts |
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|
MathVista |
Mathematical reasoning in visual contexts |
Gemini 1.5 Flash-8B (Oct 2024) 54.7% |
Gemini 1.5 Flash (May 2024) 58.4% |
Gemini 1.5 Flash (Sep 2024) 65.8% |
Gemini 1.5 Pro (May 2024) 63.9% |
Gemini 1.5 Pro (Sep 2024) 68.1% |
|
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Audio FLEURS (55 lang) Automatic speech recognition (based on word error rate, lower is better) |
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|
Audio |
FLEURS (55 lang) |
Automatic speech recognition (based on word error rate, lower is better) |
Gemini 1.5 Flash-8B (Oct 2024) 13.6% |
Gemini 1.5 Flash (May 2024) 9.8% |
Gemini 1.5 Flash (Sep 2024) 9.6% |
Gemini 1.5 Pro (May 2024) 6.5% |
Gemini 1.5 Pro (May 2024) 6.7% |
|
Video Video-MME Video analysis across multiple domains |
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|
Video |
Video-MME |
Video analysis across multiple domains |
Gemini 1.5 Flash-8B (Oct 2024) 66.2% |
Gemini 1.5 Flash (May 2024) 74.7% |
Gemini 1.5 Flash (Sep 2024) 76.1% |
Gemini 1.5 Pro (May 2024) 77.9% |
Gemini 1.5 Pro (May 2024) 78.6% |
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Safety XSTest Measures how often models refuse to respond to safe/benign prompts. The score represents how frequently models correctly fulfill requests |
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Safety |
XSTest |
Measures how often models refuse to respond to safe/benign prompts. The score represents how frequently models correctly fulfill requests |
Gemini 1.5 Flash-8B (Oct 2024) 92.6% |
Gemini 1.5 Flash (May 2024) 86.9% |
Gemini 1.5 Flash (Sep 2024) 97.0% |
Gemini 1.5 Pro (May 2024) 88.4% |
Gemini 1.5 Pro (May 2024) 98.8% |
Try Gemini 1.5 Pro
Get started
Example prompts for the Gemini API in Google AI Studio.
Research Assistant
Understand the key attributes of a research paper’s methodology.
Plant care
How do I best care for this plant?
Which shape comes next?
Given a series of shapes, guess which comes next.
Game Character Brainstorming
Create a character design based on a provided context.
Cook Helper
Get recipe ideas based on an image of the ingredients you have on hand.
Barista Bot
Order common coffee drinks from this virtual barista.
Research
Technical reports
For developers
Build with Gemini
Integrate Gemini models into your applications with Google AI Studio and Google Cloud Vertex AI.
