Google: Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image)

Origin

google/gemini-3.1-flash-lite-image

Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) is Google's fastest, most cost-efficient Gemini image model, built for high-velocity developer pipelines and rapid-fire visual exploration. It delivers text-to-image generation...

Context

66K

Input MA / 1M

0.3

Output MA / 1M

1.8

Billing follows the provider's own reported cost rather than the catalogue price — cached input is cheaper, and reasoning tokens bill as output. Your usage page is the record of what you actually paid.

Capabilities

ChatReasoningVisionImage gen

Call it

Every model goes through the same endpoint — just use this page's ID as model.

curl https://macdecloud.com/v1/chat/completions \
  -H "Authorization: Bearer dcld-sk-..." \
  -H "Content-Type: application/json" \
  -d '{"model":"google/gemini-3.1-flash-lite-image","messages":[{"role":"user","content":"Hello"}]}'

Streaming

Add "stream": true for token-by-token output over standard SSE.

curl -N https://macdecloud.com/v1/chat/completions \
  -H "Authorization: Bearer dcld-sk-..." \
  -H "Content-Type: application/json" \
  -d '{"model":"google/gemini-3.1-flash-lite-image","stream":true,"messages":[{"role":"user","content":"hi"}]}'

Reasoning tokens are billed

This is a reasoning model: it produces a thinking pass before answering, and those tokens are billed as output — often far more of them than the answer itself. Two consequences. Too small a max_tokens gets consumed during reasoning and returns finish_reason: "length" with a null content, which looks like a failure but is just an exhausted budget (2000+ is a safer floor). And cost runs well above a non-reasoning model at the same headline price.

Image input

Make content an array mixing text and image_url parts. The image can be a public URL or a data: base64 payload.

{
  "model": "google/gemini-3.1-flash-lite-image",
  "messages": [{
    "role": "user",
    "content": [
      { "type": "text", "text": "What is in this image?" },
      { "type": "image_url", "image_url": { "url": "https://example.com/photo.jpg" } }
    ]
  }]
}

Use it from Claude Code / Cursor / opencode →