Google DeepMind (Gemini) / gemini-3-1-flash-lite
Gemini 3.1 Flash-Lite stands out for Gemini efficiency tier for speed and scale and 1M multimodal context with a lower-cost profile. It is best suited to high-volume classification and extraction and cost-aware multimodal assistants.
Context
1M
token
Input
$0.225
/ 1M tokens
Output
$1.35
/ 1M tokens
Quality
—
No score
Overview
Gemini 3.1 Flash-Lite stands out for Gemini efficiency tier for speed and scale and 1M multimodal context with a lower-cost profile. It is best suited to high-volume classification and extraction and cost-aware multimodal assistants.
Multimodal
Supports mixed text-image input and can use a 1M-token context window for longer material.
Tool calling
Can call tools or functions, so product flows can connect model output to backend actions.
Streaming
Supports streamed responses for chat, assistants, and interfaces that need visible incremental output.
Prompt cache
Supports prompt caching patterns for repeated context and longer production conversations.
Reasoning
Better suited for multi-step analysis, planning, and tasks that need deliberate reasoning.
Structured output
Can return machine-readable structures for extraction, automation, and application logic.
Model maker
Google DeepMind (Gemini)
Called through SeaLink's unified account, balance, and OpenAI-compatible API.
Protocol
OpenAI-compatible Chat Completions
Base URL: https://api.sealink.io/v1
Pricing
Light production run
100K input + 25K output
$0.0563
Higher-volume run
1M input + 250K output
$0.5625
The final charge follows generated usage and the applicable selector, such as resolution, duration, input type, or provider unit.
API
model
gemini-3-1-flash-litebase_url
https://api.sealink.io/v1Auth
Bearer $SEALINK_API_KEYcurl https://api.sealink.io/v1/chat/completions \-H "Authorization: Bearer $SEALINK_API_KEY" \-H "Content-Type: application/json" \-d '{"model": "gemini-3-1-flash-lite","messages": [{"role": "user", "content": "Hello."}]}'
from openai import OpenAIclient = OpenAI(base_url="https://api.sealink.io/v1", api_key="<your-sealink-key>")resp = client.chat.completions.create(model="gemini-3-1-flash-lite",messages=[{"role": "user", "content": "Hello."}],)print(resp.choices[0].message.content)
import OpenAI from "openai";const client = new OpenAI({baseURL: "https://api.sealink.io/v1",apiKey: process.env.SEALINK_API_KEY,});const resp = await client.chat.completions.create({model: "gemini-3-1-flash-lite",messages: [{ role: "user", content: "Hello." }],});console.log(resp.choices[0].message.content);