Model · NVIDIA

Nemotron 3.5 Super VL

Nemotron 3.5 Super VL is served by NVIDIA through OpenRouter. It provides 1.05M tokens of context and supports text, vision, video inputs.

Snapshot 2026-10-16 nvidia/nemotron-3.5-super-vl

Context window

1.05M tokens

Input / 1M tokens

$0.150

Output / 1M tokens

$0.500

Key facts

Provider	NVIDIA
OpenRouter ID	`nvidia/nemotron-3.5-super-vl`
Modalities	Text, Vision, Video
Best for	Multimodal, Budget, Long Context

Source openrouter.ai/api/v1/models Verified 2026-10-16 Drift-checked daily 06:00 CST

Best-fit workloads

Best for long context

Large context window for documents and transcripts.

Best for budget

Low input/output cost for high-volume workloads.

Best multimodal

Handles images, files, audio or video inputs.

Cost estimates

These examples use the 2026-10-16 input and output prices. Cache discounts, provider surcharges and tool fees are excluded.

Workload	Input	Output	Estimated cost
Quick test	20,000	5,000	$0.005
Product chat month	500,000	125,000	$0.138
Document batch	5,000,000	1,000,000	$1.25

Strengths

✓ Open weights (nvidia/NVIDIA-Nemotron-3.5-Super-VL): 12B active parameters out of 120B, and a 1M-token window
✓ Reads video and images as well as text at $0.15 / $0.50 per million
✓ A 235,929-token output ceiling, far past what the flagship Flash rows allow

Limitations

! Artificial Analysis puts it at 26 on its index — a cheap multimodal reader, not a frontier reasoner
! Text output only
! The free route is a separate listing with a 1,000,000-token window and a 131,072-token output cap, so the two are not interchangeable

OpenRouter API quickstart

Run these examples from your server or edge function. Keep the OpenRouter API key private and do not expose it in browser code.

cURL

curl https://openrouter.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $OPENROUTER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "nvidia/nemotron-3.5-super-vl",
    "messages": [{ "role": "user", "content": "Summarize this document in five bullet points." }],
    "max_tokens": 500
  }'

JavaScript / TypeScript

const response = await fetch("https://openrouter.ai/api/v1/chat/completions", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.OPENROUTER_API_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    model: "nvidia/nemotron-3.5-super-vl",
    messages: [{ role: "user", content: "Summarize this document in five bullet points." }],
    max_tokens: 500,
  }),
});

const data = await response.json();
console.log(data.choices[0].message.content);

How to evaluate Nemotron 3.5 Super VL

Run five real tasks from your product, not generic demo prompts.
Record token usage, latency and output quality.
Estimate cost using your real input/output mix.
Compare it against one model with a similar price and one stronger model.

Compare models View on OpenRouter ↗