> ## AI Agent Context
> Get the complete documentation index at: https://aistudio.google.com/llms.txt
> Use this file to discover all available pages.
> For the full documentation in a single file, fetch: https://aistudio.google.com/llms-full.txt

# Getting a model

{% mark class="http-get" %}{% icon name="south_west" /%}`GET`{% /mark %} `https://generativelanguage.googleapis.com/v1beta/models/{model}`

Gets information about a specific [`Model`](/api-reference/models#Resource:Model) such as its version number, token
limits,
[parameters](/docs/prompting-strategies#model-parameters)
and other metadata. Refer to the [Gemini models
guide](/docs/models) for detailed
model information.

{% two-column-layout %}
  {% left-column %}
## Parameters  {% class="hide-from-toc" id="parameters" %}

  {% section class="api-ref-property-list" %}
  **model**: {% mark %}required{% /mark %} `string`

  The model ID, for example `gemini-2.5-flash`. Forms the resource name `models/{model}`.

  {% /section %}

  {% /left-column %}

  {% right-column class="sticky" %}
  **Example request** {% class="example-heading" %}

  {% tabs %}
  {% tab label="REST" %}
  ```sh
  curl https://generativelanguage.googleapis.com/v1beta/models/gemini-3.8-flash?key=$GEMINI_API_KEY
  ```

  {% /tab %}

  {% tab label="Python" %}
  ```python
  from google import genai
  
  client = genai.Client()
  model_info = client.models.get(model="gemini-3.8-flash")
  print(model_info)
  ```

  {% /tab %}

  {% tab label="Go" %}
  ```go
  ctx := context.Background()
  client, err := genai.NewClient(ctx, &genai.ClientConfig{
      APIKey:  os.Getenv("GEMINI_API_KEY"),
      Backend: genai.BackendGeminiAPI,
  })
  if err != nil {
      log.Fatal(err)
  }
  
  modelInfo, err := client.Models.Get(ctx, "gemini-3.8-flash", nil)
  if err != nil {
      log.Fatal(err)
  }
  
  fmt.Println(modelInfo)
  ```

  {% /tab %}

  {% /tabs %}

  {% /right-column %}

{% /two-column-layout %}

## Response  {% class="hide-from-toc" id="response" %}

{% section class="api-ref-property-list" %}
  **name**: {% mark %}required{% /mark %} `string`

  The resource name of the [`Model`](/api-reference/models#Resource:Model). Refer to [Model variants](/docs/models#model-versions) for all allowed values. Format: `models/{model}` with a `{model}` naming convention of:

  - "{base_model_id}-{version}"

  Examples:

  - `models/gemini-1.5-flash-001`

  {% hr /%}

  **baseModelId**: {% mark %}required{% /mark %} `string`

  The name of the base model, pass this to the generation request. Examples:

  - `gemini-1.5-flash`

  {% hr /%}

  **version**: {% mark %}required{% /mark %} `string`

  The version number of the model. This represents the major version (`1.0` or `1.5`)

  {% hr /%}

  **displayName**: `string`

  The human-readable name of the model. E.g. "Gemini 1.5 Flash". The name can be up to 128 characters long and can consist of any UTF-8 characters.

  {% hr /%}

  **description**: `string`

  A short description of the model.

  {% hr /%}

  **inputTokenLimit**: `integer`

  Maximum number of input tokens allowed for this model.

  {% hr /%}

  **outputTokenLimit**: `integer`

  Maximum number of output tokens available for this model.

  {% hr /%}

  **supportedGenerationMethods**: `string array`

  The model's supported generation methods. The corresponding API method names are defined as Pascal case strings, such as `generateMessage` and `generateContent`.

  {% hr /%}

  **temperature**: `number`

  Controls the randomness of the output. Values can range over `[0.0,max_temperature]`, inclusive. A higher value will produce responses that are more varied, while a value closer to `0.0` will typically result in less surprising responses from the model. This value specifies default to be used by the backend while making the call to the model.

  {% hr /%}

  **maxTemperature**: `number`

  The maximum temperature this model can use.

  {% hr /%}

  **topP**: `number`

  For [Nucleus sampling](/docs/prompting-strategies#model-parameters). Nucleus sampling considers the smallest set of tokens whose probability sum is at least `top_p`. This value specifies default to be used by the backend while making the call to the model.

  {% hr /%}

  **topK**: `integer`

  For Top-k sampling. Top-k sampling considers the set of `top_k` most probable tokens. This value specifies default to be used by the backend while making the call to the model. If empty, indicates the model doesn't use top-k sampling, and `top_k` isn't allowed as a generation parameter.

  {% hr /%}

  **thinking**: `boolean`

  Whether the model supports thinking.

{% /section %}