OctopusX

Google

Latency—

Throughput—

Upload rate—

Context length1048576 tokens

Max output65536 tokens

Input price$0.5per 1M tokens

Output price$3per 1M tokens

Cache read$0.05per 1M tokens

Cache write—per 1M tokens

Performance

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Code Example

curl ${API_BASE_URL}/v1beta/models/gemini-3-flash-preview:generateContent \
  -H "Authorization: Bearer <YOUR_API_KEY>" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-3-flash-preview",
    "messages": [
      {
        "role": "user",
        "content": "Hello"
      }
    ]
  }'

Replace <YOUR_API_KEY> with the API key generated on your token management page.

Authentication

All requests must include the Authorization: Bearer <TOKEN> header.

Endpoint Path

POST

google-generate-content

Supported Parameters

ParameterTypeDefaultDescription

boolean-Deprecated alias for reasoning.exclude. When true, reasoning tokens are returned in the response when supported by the model.

integer-This sets the upper limit for the number of tokens the model can generate in response. It won't produce more than this limit. The maximum value is the context length minus the prompt length.

map-Controls reasoning behavior for models that support thinking tokens, including whether reasoning is enabled, the reasoning effort, maximum reasoning tokens, and whether reasoning is excluded from the response.

map-Forces the model to produce specific output format. Setting to `{ "type": "json_object" }` enables JSON mode, which guarantees the message the model generates is valid JSON. **Note**: when using JSON mode, you should also instruct the model to produce JSON yourself via a system or user message.

integer-If specified, the inferencing will sample deterministically, such that repeated requests with the same seed and parameters should return the same result. Determinism is not guaranteed for some models.

array-Stop generation immediately if the model encounter any token specified in the stop array.

boolean-If the model can return structured outputs using response\_format json\_schema.

float1.0This setting influences the variety in the model's responses. Lower values lead to more predictable and typical responses, while higher values encourage more diverse and less common responses. At 0, the model always gives the same response for a given input.

string or object-Controls which (if any) tool is called by the model. 'none' means the model will not call any tool and instead generates a message. 'auto' means the model can pick between generating a message or calling one or more tools. 'required' means the model must call one or more tools. Specifying a particular tool via `{"type": "function", "function": {"name": "my_function"}}` forces the model to call that tool.

array-Tool calling parameter, following OpenAI's tool calling request shape. For non-OpenAI providers, it will be transformed accordingly. [Click here to learn more about tool calling](/docs/guides/features/tool-calling)

float1.0This setting limits the model's choices to a percentage of likely tokens: only the top tokens whose probabilities add up to P. A lower value makes the model's responses more predictable, while the default setting allows for a full range of token choices. Think of it like a dynamic Top-K.

Rate Limits

GroupRPMTPMRPD

RPM = requests per minute, TPM = tokens per minute, RPD = requests per day. Limits apply by token group.

Pricing

ProviderBilling typePrice summary

G

Gemini

Per token