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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.

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.

Capability

Benchmark

Description

Gemini 1.5 Flash

(May 2024)

Gemini 1.5 Flash

(Sep 2024)

Gemini 1.5 Pro

(May 2024)

Gemini 1.5 Pro

(Sep 2024)

General

MMLU-Pro

Enhanced version of popular MMLU dataset with questions across multiple subjects with higher difficulty tasks

General

MMLU-Pro

Enhanced version of popular MMLU dataset with questions in 57 subjects (incl. STEM, humanities, and others) with higher difficulty tasks

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

(May 2024)

75.8%

Code

Natural2Code

Code generation across Python, Java, C++, JS, Go . Held out dataset HumanEval-like, not leaked on the web

Code

Natural2Code

Code generation across Python, Java, C++, JS, Go . Held out dataset HumanEval-like, not leaked on the web

Gemini 1.5 Flash

(May 2004)

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)

Math

MATH

Challenging math problems (incl. algebra, geometry, pre-calculus, and others)

Gemini 1.5 Flash

(May 2004)

54.9%

Gemini 1.5 Flash

(Sep 2024)

77.9%

Gemini 1.5 Pro

(May 2024)

67.7%

Gemini 1.5 Pro

86.5%

HiddenMath

Competition-level math problems, Held out dataset AIME/AMC-like, crafted by experts and not leaked on the web

HiddenMath

Competition-level math problems, Held out dataset AIME/AMC-like, crafted by experts and not leaked on the web

Gemini 1.5 Flash

(May 2004)

20.3%

Gemini 1.5 Flash

(Sep 2024)

47.2%

Gemini 1.5 Pro

(May 2024)

28.0%

Gemini 1.5 Pro

52.0%

Reasoning

GPQA (diamond)

Challenging dataset of questions written by domain experts in biology, physics, and chemistry

Reasoning

GPQA (diamond)

Challenging dataset of questions written by domain experts in biology, physics, and chemistry

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

Multilingual

WMT23

Language translation

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

RULER (at 1M)

Diagnostic suite checking long-context ability of the models over a range of tasks

Long Context

RULER (at 1M)

Diagnostic suite checking long-context ability of the models over a range of tasks

Gemini 1.5 Flash

(May 2024)

69.6%

Gemini 1.5 Flash

(Sep 2024)

82.3%

Gemini 1.5 Pro

(May 2024)

40.1%

Gemini 1.5 Pro

(Sep 2024)

86.4%

MRCR (1M)

Diagnostic long-context understanding evaluation

MRCR (1M)

Diagnostic long-context understanding evaluation

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 reasoning problems

Image

MMMU

Multi-discipline college-level reasoning problems

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

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

(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%

Image

MathVista

Mathematical reasoning in visual contexts

MathVista

Mathematical reasoning in visual contexts

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%

Audio

FLEURS (55 languages)

Automatic speech recognition (based on word error rate, lower is better)

Audio

FLEURS (55 languages)

Automatic speech recognition (based on word error rate, lower is better)

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

Video

Video-MME

Video analysis across multiple domains

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%

Safety

XSTest

Measures how often models refuse to respond to safe/benign prompts. The score represents how frequently models correctly fulfill requests

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

(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

Technical reports

For developers

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