About
The smallest model in the Ministral 3 family, Ministral 3 3B is a powerful, efficient tiny language model with vision capabilities.
Pricing
| Input | $0.14 | per 1M prompt tokens |
|---|---|---|
| Output | $0.14 | per 1M generated tokens, reasoning included |
| Cached input | $0.01 | per 1M tokens read back from the prompt cache |
What a request costs
| Typical request | Each | Per 1,000 |
|---|---|---|
| Short chat reply1,500 in · 400 out | $0.0003 | $0.266 |
| Question over a long document40,000 in · 800 out | $0.0057 | $5.71 |
| Agent tool step20,000 in · 1,200 out | $0.0030 | $2.97 |
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
- #1163DModel arenaElo 96336% wins
- #120CodeModel arenaElo 101237% wins
- #122WebsitesModel arenaElo 102938% wins
- #126Game devModel arenaElo 95233% 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": "mistralai/ministral-3b-2512",
"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="mistralai/ministral-3b-2512",
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: "mistralai/ministral-3b-2512",
messages: [{ role: "user", content: "Hello" }],
});
console.log(reply.choices[0].message.content);
Parameters this model accepts
frequency_penaltymax_tokenspresence_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_p