import requests r = requests.post( "https://api.aimlapi.com/v1/chat/completions", headers={"Authorization": "Bearer " + AIMLAPI_KEY}, json={ "model": "google/gemini-3.1-pro-preview-customtools", "messages": [ { "role": "user", "content": "Hello!" } ] }, ) print(r.json())
const r = await fetch("https://api.aimlapi.com/v1/chat/completions", { method: "POST", headers: { Authorization: `Bearer ${process.env.AIMLAPI_KEY}`, "Content-Type": "application/json", }, body: JSON.stringify({ "model": "google/gemini-3.1-pro-preview-customtools", "messages": [ { "role": "user", "content": "Hello!" } ] }), }); console.log(await r.json());
curl -X POST https://api.aimlapi.com/v1/chat/completions \ -H "Authorization: Bearer $AIMLAPI_KEY" \ -H "Content-Type: application/json" \ -d '{"model":"google/gemini-3.1-pro-preview-customtools","messages":[{"role":"user","content":"Hello!"}]}'
OpenAI-compatible — swap the base URL and it works with your existing SDK.
| Type | Price |
|---|---|
| Input | |
| Output | |
| Cached input |
| Model | Input | Output | Context | Best for |
|---|---|---|---|---|
Gemini 3.1 Pro Preview Custom Tools This page | Reasoning + agents | |||
| Reasoning + agents | ||||
| Balanced coding + agents | ||||
| Long-context, multimodal & agentic workflows | ||||
| Reasoning + agents |
Gemini 3.1 Pro Preview Custom Tools has a 1,048,756 tokens context window and can return up to 65,536 tokens.
Gemini 3.1 Pro Preview Custom Tools takes image, text as input and returns text.
Use google/gemini-3.1-pro-preview-customtools as the model id. Requests go to https://api.aimlapi.com/v1/chat/completions.
Gemini 3.1 Pro Preview Custom Tools is priced at input $2.7508 / 1M tokens, output $16.5048 / 1M tokens, cached input $0.27508 / 1M tokens.
Yes, Gemini 3.1 Pro Preview Custom Tools can stream responses as they are generated.
Yes, Gemini 3.1 Pro Preview Custom Tools accepts image input alongside text.
Gemini 3.1 Pro Preview Custom Tools was built by Google.
It supports function calling, reasoning, structured outputs, web search, and parallel tool calls, making it suited for tasks that combine multi-step reasoning with tool use.