Gemini models

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 sizes

The following table shows the available sizes and what they mean relative to each other.

Model size Description Services
Gemini 1.0 Pro A model size that balances capability and efficiency.
  • text
  • chat

Model versions

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.

For models that have a stable version, see the "Model names" row for the model in Model variations.

Model variations

The Gemini API offers different models optimized for specific use cases. The following table describes attributes of each.

Variation Attribute Description
Gemini 1.5 Pro (Preview only) Model last updated April 2024
Model code models/gemini-1.5-pro-latest
Model capabilities
  • Input: text and image
  • Output: text
  • Optimized for language tasks such as:
    • Code generation
    • Text generation
    • Text editing
    • Problem solving
    • Recommendations generation
    • Information extraction
    • Data extraction or generation
    • AI agent
  • Can handle zero, one, and few-shot tasks.
Supported generation methods generateContent
Input token limit 1048576
Output token limit 8192
Model safety Automatically applied safety settings which are adjustable by developers. See the safety settings topic for details.
Rate limit 2 queries per minute, 1000 queries per day [1]
Gemini Pro Model last updated February 2024
Model code models/gemini-pro
Model capabilities
  • Input: text
  • Output: text
  • Generates text.
  • Can handle multi-turn conversational format.
  • Can handle zero, one, and few-shot tasks.
Supported generation methods generateContent
Input token limit 30720
Output token limit 2048
Model safety Automatically applied safety settings which are adjustable by developers. See the safety settings topic for details.
Rate limit 60 requests per minute [1]
Model names
  • Latest version: gemini-1.0-pro-latest
  • Latest stable version: gemini-1.0-pro
  • Stable versions:
    • gemini-1.0-pro-001
Gemini 1.0 Pro Vision Model last updated December 2023
Model code models/gemini-pro-vision
Model capabilities
  • Input: text and images
  • Output: text
  • Can take multimodal inputs, text and image.
  • Can handle zero, one, and few-shot tasks.
Supported generation methods generateContent
Input token limit 12288
Output token limit 4096
Model safety Automatically applied safety settings which are adjustable by developers. See the safety settings topic for details.
Rate limit 60 requests per minute [1]
Embedding Model last updated December 2023
Model code models/embedding-001
Model capabilities
  • Input: text
  • Output: text
  • Generates text embeddings for the input text.
  • Optimized for creating embeddings for text of up to 2048 tokens.
Supported generation methods embedContent
Model safety No adjustable safety settings.
Rate limit 1500 requests per minute [1]
Text Embedding Model last updated April 2024
Model code models/text-embedding-004 (text-embedding-preview-0409 in Vertex AI)
Model capabilities
  • Input: text
  • Output: text
  • Generates text embeddings for the input text.
  • Supports elastic embedding sizes under 768.
Supported generation methods embedContent
Model safety No adjustable safety settings.
Rate limit 1500 requests per minute [1]
AQA Model last updated December 2023
Model code models/aqa
Model capabilities
  • Input: text
  • Output: text
  • Model that performs Attributed Question Answering.
  • Model trained to return answers to questions that are grounded in provided sources, along with estimating answerable probability.
Supported generation methods generateAnswer
Supported languages English
Input token limit 7168
Output token limit 1024
Model safety Automatically applied safety settings which are adjustable by developers. See the safety settings topic for details.
Rate limit 60 requests per minute [1]

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

Model metadata

Use the ModelService API to get additional metadata about the latest models such as input and output token limits. The following table displays the metadata for the Gemini Pro model variant.

Attribute Value
Display name Gemini 1.0 Pro
Model code models/gemini-1.0-pro
Description Model targeted for text generation
Supported generation methods generateContent
Temperature 0.9
top_p 1
top_k 1

Model attributes

The following table describes the attributes of the Gemini models which are common to all model variations.

Attribute Description
Training data Gemini's knowledge cutoff is early 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

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

See the model parameters section of the Intro to LLMs guide for information about each of these parameters.

Next steps