About
Gemini 3 Flash Preview is a high speed, high value thinking model designed for agentic workflows, multi turn chat, and coding assistance.
Pricing
| Input | $0.35 | per 1M prompt tokens |
|---|---|---|
| Output | $2.10 | per 1M generated tokens, reasoning included |
| Web search | $0.020 | per request that uses the provider’s built-in search |
What a request costs
| Typical request | Each | Per 1,000 |
|---|---|---|
| Short chat reply1,500 in · 400 out | $0.0014 | $1.36 |
| Question over a long document40,000 in · 800 out | $0.016 | $15.68 |
| Agent tool step20,000 in · 1,200 out | $0.0095 | $9.52 |
At the developer-API rate, before any provider promotion or prompt-cache saving. In the app, the model picker shows what a message costs on your plan before you send it.
Benchmarks
Head-to-head rankings
- #8SlidesAgent arenaElo 107339% wins
- #19Godot gamesAgent arenaElo 116151% wins
- #33Android appsAgent arenaElo 106648% wins
- #33Full stackAgent arenaElo 106347% wins
- #34Web appsAgent arenaElo 110449% wins
- #39Mobile appsAgent arenaElo 108747% wins
- #553DModel arenaElo 118463% wins
- #60CodeModel arenaElo 119158% wins
- #60WebsitesModel arenaElo 119857% wins
- #66Game devModel arenaElo 116958% wins
Scores from Artificial Analysis; bars are scaled to the best model on our list. Rankings from Design Arena head-to-head votes. Published by OpenRouter alongside its catalogue.
Call it from code
OpenAI-compatible: point any OpenAI SDK at https://api.privateer.pro/v1 and set
model. Keys are created in the app under Settings.
curl https://api.privateer.pro/v1/chat/completions \
-H "Authorization: Bearer $PRIVATEER_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "google/gemini-3-flash-preview:batch",
"messages": [{ "role": "user", "content": "Hello" }],
"reasoning": { "effort": "medium" }
}'
import os
from openai import OpenAI
client = OpenAI(
base_url="https://api.privateer.pro/v1",
api_key=os.environ["PRIVATEER_API_KEY"],
)
reply = client.chat.completions.create(
model="google/gemini-3-flash-preview:batch",
messages=[{"role": "user", "content": "Hello"}],
)
print(reply.choices[0].message.content)
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api.privateer.pro/v1",
apiKey: process.env.PRIVATEER_API_KEY,
});
const reply = await client.chat.completions.create({
model: "google/gemini-3-flash-preview:batch",
messages: [{ role: "user", content: "Hello" }],
});
console.log(reply.choices[0].message.content);
Parameters this model accepts
include_reasoningmax_tokensreasoningreasoning_effortresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_p