About
DeepSeek V4 Pro is a large-scale Mixture-of-Experts model from DeepSeek with 1.6T total parameters and 49B activated parameters, supporting a 1M-token context window.
Pricing
| Input | $1.34 from $0.63 | per 1M prompt tokens |
|---|---|---|
| Output | $2.67 | per 1M generated tokens, reasoning included |
| Cached input | $0.11 | per 1M tokens read back from the prompt cache |
45% off right now. The provider is running a promotion, and the developer API bills what the provider actually charged for your call plus our flat markup, so it reaches your bill with nothing to claim. The “from” figure is the cheapest endpoint serving the model; which one answers is the provider’s routing decision, so treat it as a floor. Promotions can end at any time.
What a request costs
| Typical request | Each | Per 1,000 |
|---|---|---|
| Short chat reply1,500 in · 400 out | $0.0031 | $3.08 |
| Question over a long document40,000 in · 800 out | $0.056 | $55.63 |
| Agent tool step20,000 in · 1,200 out | $0.030 | $29.96 |
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
- #303DModel arenaElo 125457% wins
- #32Godot gamesAgent arenaElo 105934% wins
- #41Game devModel arenaElo 123252% wins
- #42Web appsAgent arenaElo 100026% wins
- #43Full stackAgent arenaElo 94822% wins
- #43ASCII artModel arenaElo 115146% wins
- #44CodeModel arenaElo 124252% wins
- #49SVGModel arenaElo 113945% wins
- #49WebsitesModel arenaElo 123651% wins
- #50UI componentsModel arenaElo 122151% 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": "deepseek/deepseek-v4-pro",
"messages": [{ "role": "user", "content": "Hello" }],
"reasoning": { "effort": "xhigh" }
}'
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="deepseek/deepseek-v4-pro",
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: "deepseek/deepseek-v4-pro",
messages: [{ role: "user", content: "Hello" }],
});
console.log(reply.choices[0].message.content);
Parameters this model accepts
frequency_penaltyinclude_reasoninglogit_biaslogprobsmax_completion_tokensmax_tokensmin_ppresence_penaltyreasoningreasoning_effortrepetition_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_ktop_logprobstop_p