Starting April 29, 2025, Gemini 1.5 Pro and Gemini 1.5 Flash models are not available in projects that have no prior usage of these models, including new projects. For details, see Model versions and lifecycle.
When you open the model card for a supported model, a Try out panel is
embedded in the card. You can quickly test the model's capabilities by sending a
text prompt in the Try out panel. The Try out panel also lets you set
some of the most common parameters such as temperature and number of output
tokens.
Supported models
The following models have demo playgrounds available.
Provider
Models
Google
Gemma 2 2B it (instruction tuned)
Gemma 2 9B it (instruction tuned)
Gemma 2 27B it (instruction tuned)
Gemma 2B
Gemma 2B it (instruction tuned)
Gemma 7B
Gemma 7B it (instruction tuned)
Meta
Llama 3 8B Instruct
Llama 3 70B Instruct
Llama 2 7B
Llama 2 7B Chat
Llama 2 13B Chat
Llama 2 70B Chat (Int8)
Code Llama 7B Python
TII
Falcon 7B
Mistral AI
Mixtral 8x7B
Before you begin
This tutorial requires you to set up a Google Cloud project and enable the
Vertex AI API.
Sign in to your Google Cloud account. If you're new to
Google Cloud,
create an account to evaluate how our products perform in
real-world scenarios. New customers also get $300 in free credits to
run, test, and deploy workloads.
In the Google Cloud console, on the project selector page,
select or create a Google Cloud project.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-27 UTC."],[],[],null,["# Try it: Test model capabilities using demo playgrounds in Model Garden\n\nModel Garden hosts public demo playgrounds for\n[supported models](#supported_models). The playgrounds are powered by predeployed\nVertex AI [online prediction endpoints](/vertex-ai/docs/predictions/overview).\n\nWhen you open the model card for a supported model, a **Try out** panel is\nembedded in the card. You can quickly test the model's capabilities by sending a\ntext prompt in the **Try out** panel. The **Try out** panel also lets you set\nsome of the most common parameters such as temperature and number of output\ntokens.\n\nSupported models\n----------------\n\nThe following models have demo playgrounds available.\n\nBefore you begin\n----------------\n\nThis tutorial requires you to set up a Google Cloud project and enable the\nVertex AI API.\n\n- Sign in to your Google Cloud account. If you're new to Google Cloud, [create an account](https://console.cloud.google.com/freetrial) to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.\n- In the Google Cloud console, on the project selector page,\n select or create a Google Cloud project.\n\n | **Note**: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.\n\n [Go to project selector](https://console.cloud.google.com/projectselector2/home/dashboard)\n-\n [Verify that billing is enabled for your Google Cloud project](/billing/docs/how-to/verify-billing-enabled#confirm_billing_is_enabled_on_a_project).\n\n-\n\n\n Enable the Vertex AI API.\n\n\n [Enable the API](https://console.cloud.google.com/flows/enableapi?apiid=aiplatform.googleapis.com)\n\n- In the Google Cloud console, on the project selector page,\n select or create a Google Cloud project.\n\n | **Note**: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.\n\n [Go to project selector](https://console.cloud.google.com/projectselector2/home/dashboard)\n-\n [Verify that billing is enabled for your Google Cloud project](/billing/docs/how-to/verify-billing-enabled#confirm_billing_is_enabled_on_a_project).\n\n-\n\n\n Enable the Vertex AI API.\n\n\n [Enable the API](https://console.cloud.google.com/flows/enableapi?apiid=aiplatform.googleapis.com)\n\n\u003cbr /\u003e\n\nTry out Gemma 2\n---------------\n\nIn this quickstart, you try out the `Gemma-2b-it` model. Note that\n`-it` stands for [instruction-tuned](/vertex-ai/generative-ai/docs/open-models/use-gemma#gem-model-sizes).\n\n1. In the Google Cloud console, go to the **Gemma 2** model card.\n\n [Go to Gemma 2](https://console.cloud.google.com/vertex-ai/publishers/google/model-garden/gemma2)\n2. In the **Try out** panel:\n\n 1. For **Region**, accept the default or choose your region.\n 2. For **Endpoint** , select **Demo playground (Free)2b-it**.\n 3. In the **Prompt** box, enter `Why is the sky blue?`.\n 4. Expand the **Advanced options** section and view the default parameters.\n\n3. Click **Submit**. The output appears below the Submit button.\n\nClean up\n--------\n\nTo avoid incurring charges to your Google Cloud account for the resources used\non this page, follow these steps.\n\n### Delete the project\n\n\nThe easiest way to eliminate billing is to delete the project that you\ncreated for the tutorial.\n\nTo delete the project:\n\n| **Caution** : Deleting a project has the following effects:\n|\n| - **Everything in the project is deleted.** If you used an existing project for the tasks in this document, when you delete it, you also delete any other work you've done in the project.\n| - **Custom project IDs are lost.** When you created this project, you might have created a custom project ID that you want to use in the future. To preserve the URLs that use the project ID, such as an `appspot.com` URL, delete selected resources inside the project instead of deleting the whole project.\n|\n|\n| If you plan to explore multiple architectures, tutorials, or quickstarts, reusing projects\n| can help you avoid exceeding project quota limits.\n1. In the Google Cloud console, go to the **Manage resources** page.\n\n [Go to Manage resources](https://console.cloud.google.com/iam-admin/projects)\n2. In the project list, select the project that you want to delete, and then click **Delete**.\n3. In the dialog, type the project ID, and then click **Shut down** to delete the project.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\nWhat's next\n-----------\n\nSee an [overview of Model Garden](/vertex-ai/generative-ai/docs/model-garden/explore-models)."]]
