quickstarts/Models.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Tce3stUlHN0L"
      },
      "source": [
        "##### Copyright 2025 Google LLC."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "tuOe1ymfHZPu"
      },
      "outputs": [],
      "source": [
        "# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n",
        "# you may not use this file except in compliance with the License.\n",
        "# You may obtain a copy of the License at\n",
        "#\n",
        "# https://www.apache.org/licenses/LICENSE-2.0\n",
        "#\n",
        "# Unless required by applicable law or agreed to in writing, software\n",
        "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
        "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
        "# See the License for the specific language governing permissions and\n",
        "# limitations under the License."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "L5Lv3UtGCFH4"
      },
      "source": [
        "# Gemini API: List models\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nAJ9EGE2SoXm"
      },
      "source": [
        "<a target=\"_blank\" href=\"https://colab.research.google.com/github/google-gemini/cookbook/blob/main/quickstarts/Models.ipynb\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" height=30/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Gh9D-DvWSuqq"
      },
      "source": [
        "This notebook demonstrates how to list the models that are available for you to use in the Gemini API, and how to find details about a model."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "i755jXzS5kLN"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\u001b[?25l   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/137.7 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m137.7/137.7 kB\u001b[0m \u001b[31m3.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h"
          ]
        }
      ],
      "source": [
        "%pip install -U -q google-genai"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4ol10W6Q_Y-s"
      },
      "source": [
        "## Configure your API key\n",
        "\n",
        "To run the following cell, your API key must be stored it in a Colab Secret named `GOOGLE_API_KEY`. If you don't already have an API key, or you're not sure how to create a Colab Secret, see [Authentication](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Authentication.ipynb) for an example."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "id": "8PXsFZBQ_XA5"
      },
      "outputs": [],
      "source": [
        "from google.colab import userdata\n",
        "\n",
        "GOOGLE_API_KEY = userdata.get(\"GOOGLE_API_KEY\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3Al4lFhNB22n"
      },
      "source": [
        "## List models\n",
        "\n",
        "Use `list_models()` to see what models are available. These models support `generateContent`, the main method used for prompting."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "3wE76b_gBn2k"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "models/chat-bison-001\n",
            "models/text-bison-001\n",
            "models/embedding-gecko-001\n",
            "models/gemini-1.0-pro-vision-latest\n",
            "models/gemini-pro-vision\n",
            "models/gemini-1.5-pro-latest\n",
            "models/gemini-1.5-pro-001\n",
            "models/gemini-1.5-pro-002\n",
            "models/gemini-1.5-pro\n",
            "models/gemini-1.5-flash-latest\n",
            "models/gemini-1.5-flash-001\n",
            "models/gemini-1.5-flash-001-tuning\n",
            "models/gemini-1.5-flash\n",
            "models/gemini-1.5-flash-002\n",
            "models/gemini-1.5-flash-8b\n",
            "models/gemini-1.5-flash-8b-001\n",
            "models/gemini-1.5-flash-8b-latest\n",
            "models/gemini-1.5-flash-8b-exp-0827\n",
            "models/gemini-1.5-flash-8b-exp-0924\n",
            "models/gemini-2.0-flash-exp\n",
            "models/gemini-2.0-flash\n",
            "models/gemini-2.0-flash-001\n",
            "models/gemini-2.0-flash-lite-001\n",
            "models/gemini-2.0-flash-lite\n",
            "models/gemini-2.0-pro-exp\n",
            "models/gemini-2.5-pro-exp-03-25\n",
            "models/gemini-exp-1206\n",
            "models/gemini-2.0-flash-thinking-exp-01-21\n",
            "models/gemini-2.0-flash-thinking-exp\n",
            "models/gemini-2.0-flash-thinking-exp-1219\n",
            "models/learnlm-1.5-pro-experimental\n",
            "models/embedding-001\n",
            "models/text-embedding-004\n",
            "models/aqa\n",
            "models/imagen-3.0-generate-002\n"
          ]
        }
      ],
      "source": [
        "from google import genai\n",
        "\n",
        "client = genai.Client(api_key=GOOGLE_API_KEY)\n",
        "\n",
        "for model in client.models.list():\n",
        "    print(model.name)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tlguLt1yKET9"
      },
      "source": [
        "These models support `embedContent`, used for embeddings:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "lQmlIpr5JHqz"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "models/embedding-001\n",
            "models/text-embedding-004\n"
          ]
        }
      ],
      "source": [
        "for model in client.models.list():\n",
        "    if \"embedContent\" in model.supported_actions:\n",
        "        print(model.name)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nFJAyDD9QVrC"
      },
      "source": [
        "## Find details about a model\n",
        "\n",
        "You can see more details about a model, including the `input_token_limit` and `output_token_limit` as follows."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "BYYxVE4ZnoGy"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "name='models/gemini-2.0-flash' display_name='Gemini 2.0 Flash' description='Gemini 2.0 Flash' version='2.0' endpoints=None labels=None tuned_model_info=TunedModelInfo(base_model=None, create_time=None, update_time=None) input_token_limit=1048576 output_token_limit=8192 supported_actions=['generateContent', 'countTokens']\n"
          ]
        }
      ],
      "source": [
        "for model in client.models.list():\n",
        "    if model.name == \"models/gemini-2.0-flash\":\n",
        "        print(model)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "00a56cb21953"
      },
      "source": [
        "## List tuned models\n",
        "\n",
        "To retrieve all tuned models, apply a `config` and set `query_base` to `False`:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "6786759016dc"
      },
      "outputs": [],
      "source": [
        "for model in client.models.list(config={'query_base': False}):\n",
        "    print(model)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Tq7i5FAwCe1v"
      },
      "source": [
        "## Learning more\n",
        "\n",
        "* To learn how use a model for prompting, see the [Prompting](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Prompting.ipynb) quickstart.\n",
        "\n",
        "* To learn how use a model for embedding, see the [Embedding](https://github.com/google-gemini/cookbook/blob/main/quickstarts/Embeddings.ipynb) quickstart.\n",
        "\n",
        "* For more information on models, visit the [Gemini models](https://ai.google.dev/models/gemini) documentation."
      ]
    }
  ],
  "metadata": {
    "colab": {
      "name": "Models.ipynb",
      "toc_visible": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
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