Gemini

Gemini is a family of generative AI models that lets developers generate content and solve problems. These models are designed and trained to handle both text and images as input. This guide provides information about each model variant to help you decide which is the best fit for your use case.

Model variants

The Gemini API offers different models that are optimized for specific use cases. Here's a brief overview of Gemini variants that are available:

Model variant Input(s) Output Optimized for
Gemini 1.5 Pro
gemini-1.5-pro
Audio, images, videos, and text Text Complex reasoning tasks such as code and text generation, text editing, problem solving, data extraction and generation
Gemini 1.5 Flash
gemini-1.5-flash
Audio, images, videos, and text Text Fast and versatile performance across a diverse variety of tasks
Gemini 1.0 Pro
gemini-1.0-pro
Text Text Natural language tasks, multi-turn text and code chat, and code generation
(Deprecated) Gemini 1.0 Pro Vision
gemini-pro-vision
Images, videos, and text Text Visual-related tasks, like generating image descriptions or identifying objects in images
Text Embedding
text-embedding-004
Text Text embeddings Measuring the relatedness of text strings

The following table describes the attributes of the Gemini models which are common to all model variants:

Attribute Description
Training data Gemini's knowledge cutoff is November 2023. Knowledge about events after that time is limited.
Supported languages See available languages
Configurable model parameters
  • Top p
  • Top k
  • Temperature
  • Stop sequence
  • Max output length
  • Number of response candidates

See the model parameters section of the generative models guide for information about each of these parameters.

Gemini 1.5 Pro

Gemini 1.5 Pro is a mid-size multimodal model that is optimized for a wide-range of reasoning tasks such as:

  • Code generation
  • Text generation
  • Text editing
  • Problem solving
  • Recommendations generation
  • Information extraction
  • Data extraction or generation
  • Creation of AI agents

1.5 Pro can process large amounts of data at once, including 1 hour of video, 9.5 hours of audio, codebases with over 30,000 lines of code or over 700,000 words.

1.5 Pro is capable of handling zero-, one-, and few-shot learning tasks.

Model details

Property Description
Model code models/gemini-1.5-pro-latest
Inputs Audio, images, video, and text
Output Text
Supported generation methods generateContent
Input token limit[**] 1,048,576
Output token limit[**] 8,192
Maximum number of images per prompt 3,600
Maximum video length 1 hour
Maximum audio length Approximately 9.5 hours
Maximum number of audio files per prompt 1
Model safety Automatically applied safety settings which are adjustable by developers. See our page on safety settings for details.
Rate limits[*]
Free:
  • 2 RPM
  • 32,000 TPM
  • 50 RPD
  • 46,080,000 TPD
Pay-as-you-go:
  • 360 RPM
  • 2 million TPM
  • 10,000 RPD
  • 14,400,000,000 TPD
Two million context:
  • 1 RPM
  • 2 million TPM
  • 50 RPD
System instructions Supported
JSON mode Supported
Latest version gemini-1.5-pro-latest
Latest stable version gemini-1.5-pro
Stable versions gemini-1.5-pro-001
Latest update May 2024

Gemini 1.5 Flash

Gemini 1.5 Flash is a fast and versatile multimodal model for scaling across diverse tasks.

Model details

Property Description
Model code gemini-1.5-flash-latest
Input(s) Audio, images, video, and text
Output Text
Supported generation methods generateContent
Input token limit[**] 1,048,576
Output token limit[**] 8,192
Maximum number of images per prompt 3,600
Maximum video length 1 hour
Maximum audio length Approximately 9.5 hours
Maximum number of audio files per prompt 1
Model safety Automatically applied safety settings which are adjustable by developers. See our page on safety settings for details.
Rate limits[*]
Free:
  • 15 RPM
  • 1 million TPM
  • 1500 RPD
Pay-as-you-go:
  • 1000 RPM
  • 2 million TPM
System instructions Supported
JSON mode Supported
Model tuning Coming soon
Latest version gemini-1.5-flash-latest
Latest stable version gemini-1.5-flash
Stable versions gemini-1.5-flash-001
Latest update May 2024

Gemini 1.0 Pro

Gemini 1.0 Pro is an NLP model that handles tasks like multi-turn text and code chat, and code generation.

1.0 Pro is capable of handling zero-, one-, and few-shot learning tasks.

Model details

Property Description
Model code models/gemini-1.0-pro
Input Text
Output Text
Supported generation methods
Python: generate_content
REST: generateContent
Rate limits[*]
Free:
  • 15 RPM
  • 32,000 TPM
  • 1,500 RPD
  • 46,080,000 TPD
Pay-as-you-go:
  • 360 RPM
  • 120,000 TPM
  • 30,000 RPD
  • 172,800,000 TPD
System instructions Unsupported
JSON mode Unsupported
Model tuning Supported: gemini-1.0-pro-001
Latest version gemini-1.0-pro-latest
Latest stable version gemini-1.0-pro
Stable versions gemini-1.0-pro-001
Latest update February 2024

(Deprecated) Gemini 1.0 Pro Vision

Gemini 1.0 Pro Vision is a performance-optimized multimodal model that can perform visual-related tasks. For example, 1.0 Pro Vision can generate image descriptions, identify objects present in images, provide information about places or objects present in images, and more.

1.0 Pro Vision is capable of handling zero-, one-, and few-shot tasks.

Model details

Property Description
Model code models/gemini-pro-vision
Inputs Text, video, and images
Output Text
Supported generation methods
Python: generate_content
REST: generateContent
Input token limit[*] 12,288
Output token limit[*] 4,096
Maximum image size No limit
Maximum number of images per prompt 16
Maximum video length 2 minutes
Maximum number of videos per prompt 1
Model safety Automatically applied safety settings which are adjustable by developers. See our page on safety settings for details.
Rate limit[*] 60 requests per minute
Latest version gemini-1.0-pro-vision-latest
Latest stable version gemini-1.0-pro-vision
Latest update December 2023

Text Embedding and Embedding

Text Embedding

You can use the Text Embedding model to generate text embeddings for input text. For more information on the Text Embedding model, visit the Generative AI on Vertex AI documentation about text embeddings.

The Text Embedding model is optimized for creating embeddings with 768 dimensions for text of up to 2,048 tokens. Text Embedding offers elastic embedding sizes under 768. You can use elastic embeddings to generate smaller output dimensions and potentially save computing and storage costs with minor performance loss.

Model details
Property Description
Model code models/text-embedding-004 (text-embedding-preview-0409 in Vertex AI)
Input Text
Output Text embeddings
Input token limit 2,048
Output dimension size 768
Supported generation methods
Python: embed_content
REST: embedContent
Model safety No adjustable safety settings.
Rate limit[*] 1,500 requests per minute
Latest update April 2024

Embedding

You can use the Embedding model to generate text embeddings for input text.

The Embedding model is optimized for creating embeddings with 768 dimensions for text of up to 2,048 tokens.

Embedding model details
Property Description
Model code models/embedding-001
Input Text
Output Text embeddings
Input token limit 2,048
Output dimension size 768
Supported generation methods
Python: embed_content
REST: embedContent
Model safety No adjustable safety settings.
Rate limit[*] 1,500 requests per minute
Latest update December 2023

AQA

You can use the AQA model to perform Attributed Question-Answering (AQA)–related tasks over a document, corpus, or a set of passages. The AQA model returns answers to questions that are grounded in provided sources, along with estimating answerable probability.

Model details

Property Description
Model code models/aqa
Input Text
Output Text
Supported generation methods
Python: GenerateAnswerRequest
REST: generateAnswer
Supported languages English
Input token limit[**] 7,168
Output token limit[**] 1,024
Model safety Automatically applied safety settings which are adjustable by developers. See our page on safety settings for details.
Rate limit[*] 60 requests per minute
Latest update December 2023

See the examples to explore the capabilities of these model variations.

[*] A token is equivalent to about 4 characters for Gemini models. 100 tokens are about 60-80 English words.

[**] RPM: Requests per minute
TPM: Tokens per minute
RPD: Requests per day
TPD: Tokens per day

Due to capacity limitations, specified maximum rate limits are not guaranteed.

Model version name patterns

Gemini models are available in either preview or stable versions. In your code, you can use one of the following model name formats to specify which model and version you want to use.

  • Latest: Points to the cutting-edge version of the model for a specified generation and variation. The underlying model is updated regularly and might be a preview version. Only exploratory testing apps and prototypes should use this alias.

    To specify the latest version, use the following pattern: <model>-<generation>-<variation>-latest. For example, gemini-1.0-pro-latest.

  • Latest stable: Points to the most recent stable version released for the specified model generation and variation.

    To specify the latest stable version, use the following pattern: <model>-<generation>-<variation>. For example, gemini-1.0-pro.

  • Stable: Points to a specific stable model. Stable models don't change. Most production apps should use a specific stable model.

    To specify a stable version, use the following pattern: <model>-<generation>-<variation>-<version>. For example, gemini-1.0-pro-001.

Available languages

Gemini models are trained to work with the following languages:

  • Arabic (ar)
  • Bengali (bn)
  • Bulgarian (bg)
  • Chinese simplified and traditional (zh)
  • Croatian (hr)
  • Czech (cs)
  • Danish (da)
  • Dutch (nl)
  • English (en),
  • Estonian (et)
  • Finnish (fi)
  • French (fr)
  • German (de)
  • Greek (el)
  • Hebrew (iw)
  • Hindi (hi)
  • Hungarian (hu)
  • Indonesian (id)
  • Italian (it)
  • Japanese (ja)
  • Korean (ko)
  • Latvian (lv),
  • Lithuanian (lt)
  • Norwegian (no)
  • Polish (pl)
  • Portuguese (pt)
  • Romanian (ro)
  • Russian (ru)
  • Serbian (sr)
  • Slovak (sk)
  • Slovenian (sl)
  • Spanish (es)
  • Swahili (sw)
  • Swedish (sv)
  • Thai (th)
  • Turkish (tr)
  • Ukrainian (uk)
  • Vietnamese (vi)