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google/gemini-3.1-flash-image-preview

Gemini.Color

Google: gemini-3.1-flash-image-preview

Nano Banana 2 provides high-quality image generation and conversational editing at mainstream pricing, with low latency.

模式image、text → image、text
输入价格
输出价格
上下文长度131072 tokens
周消耗
上架时间2026-02-26T00:00:00Z

Google

延迟
吞吐量
上传速率
上下文长度131072 tokens
最大输出65536 tokens
上传价格每百万
输出价格每百万
缓存读取每百万
缓存写入每百万

性能统计

平均TPS
平均延迟
平均成功率
TPS
TTFT
延迟
成功率

成功率

速度

代码示例

curl ${API_BASE_URL}/v1/images/generations \
  -H "Authorization: Bearer <YOUR_API_KEY>" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-3.1-flash-image-preview",
    "prompt": "Describe the image you want"
  }'

将 <YOUR_API_KEY> 替换为你在令牌管理页面生成的 API Key。

认证方式

所有请求必须携带 Authorization: Bearer <TOKEN> 请求头。

接口路径

POST
image-generation

支持的参数

参数类型默认值说明
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.
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.

速率限制

分组RPMTPMRPD

RPM = 每分钟请求数,TPM = 每分钟 Token 数,RPD = 每天请求数。限制按令牌分组生效。

价格

分组计费类型价格摘要