About
Gemini 3.5 Flash is Google's high-efficiency multimodal model, bringing near-Pro level coding and reasoning at Flash-tier cost and speed.
Pricing
| Input | $1.05 | per 1M prompt tokens |
|---|---|---|
| Output | $6.30 | per 1M generated tokens, reasoning included |
| Cached input | $0.10 | per 1M tokens read back from the prompt cache |
| 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 | $0.0041 | $4.09 |
| Question over a long document40,000 in · 800 out | $0.047 | $47.04 |
| Agent tool step20,000 in · 1,200 out | $0.029 | $28.56 |
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
- #2SlidesAgent arenaElo 124258% wins
- #13Game devAgent arenaElo 118055% wins
- #13SVGModel arenaElo 125258% wins
- #14Android appsAgent arenaElo 119958% wins
- #16ASCII artModel arenaElo 125659% wins
- #18Full stackAgent arenaElo 119756% wins
- #20Web appsAgent arenaElo 119653% wins
- #21Mobile appsAgent arenaElo 117351% wins
- #27Game devModel arenaElo 126753% wins
- #29UI componentsModel arenaElo 127255% 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-3.5-flash:batch",
"messages": [{ "role": "user", "content": "Hello" }]
}'
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-3.5-flash: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-3.5-flash: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