Nemotron 3.5 Super VL

by NVIDIA

Zero data retentionNew
nvidia/nemotron-3.5-super-vl
Input
$0.21/1M tokens
Output
$0.70/1M tokens
Context
1Mtokens
Max output
236Ktokens
Knows to
-
Released
15 Oct 2026

About

NVIDIA Nemotron 3.5 Super VL is an open multimodal mixture-of-experts model from NVIDIA, with 12B active parameters out of 120B total.

Pricing

Input$0.21per 1M prompt tokens
Output$0.70per 1M generated tokens, reasoning included
Cached input$0.03per 1M tokens read back from the prompt cache

What a request costs

Typical requestEachPer 1,000
Short chat reply1,500 in · 400 out$0.0006$0.595
Question over a long document40,000 in · 800 out$0.0090$8.96
Agent tool step20,000 in · 1,200 out$0.0050$5.04

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

Intelligence26.5#101 of 285

Scores from Artificial Analysis; bars are scaled to the best model on our list. 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
curl https://api.privateer.pro/v1/chat/completions \
  -H "Authorization: Bearer $PRIVATEER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "nvidia/nemotron-3.5-super-vl",
    "messages": [{ "role": "user", "content": "Hello" }]
  }'
Python
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="nvidia/nemotron-3.5-super-vl",
    messages=[{"role": "user", "content": "Hello"}],
)
print(reply.choices[0].message.content)
JavaScript
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: "nvidia/nemotron-3.5-super-vl",
  messages: [{ role: "user", content: "Hello" }],
});
console.log(reply.choices[0].message.content);

Parameters this model accepts

frequency_penaltyinclude_reasoninglogit_biaslogprobsmax_tokensmin_ppresence_penaltyreasoningrepetition_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_ktop_logprobstop_p

API reference → · How API billing works →

Prices are USD at the developer-API rate, as of 16 Oct 2026, rebuilt daily from the providers’ live catalogues. ← All models