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Nemotron Model Family

A family of open models, datasets, and training recipes engineered for high performance, efficiency, and customization. Nemotron models support synthetic data workflows and supervised fine-tuning—and are optimized for real-time inference, reasoning agents, and production AI systems.

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Featured Model: nvidia/NVIDIA-Nemotron-3.5-Lightning

NVIDIA Nemotron 3.5 Lightning is NVIDIA's fastest open model for always-on agents and high-volume specialized tasks. It delivers a substantial leap in agentic capability over its predecessor Nemotron 3 Nano, with up to 4x higher throughput on a 1M-token context.

Price per 1M input tokens

$0.06

Price per 1M cached input tokens

$0.03

Price per 1M output tokens

$0.16

Release Date

09/28/2026

Context Size

262,144

# Assume openai>=1.0.0
import os

from openai import OpenAI

# Create an OpenAI client with your deepinfra token and endpoint
openai = OpenAI(
    api_key=os.environ["DEEPINFRA_API_KEY"],
    base_url="https://api.deepinfra.com/v1/openai",
)

chat_completion = openai.chat.completions.create(
    model="nvidia/NVIDIA-Nemotron-3.5-Lightning",
    messages=[{"role": "user", "content": "Hello"}],
)

print(chat_completion.choices[0].message.content)
print(chat_completion.usage.prompt_tokens, chat_completion.usage.completion_tokens)

# Hello! It's nice to meet you. Is there something I can help you with, or would you like to chat?
# 11 25
copy

Featured Model: nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B

Nemotron 3 Ultra is built for, frontier reasoning, orchestration, coding agents, deep research, and complex enterprise workflows. It delivers up to 5x faster inference and up to 30% lower cost for agentic workloads while supporting up to 1M token context.

Price per 1M input tokens

$0.50

Price per 1M cached input tokens

$0.10

Price per 1M output tokens

$2.20

Release Date

09/25/2026

Context Size

262,144

Quantization

fp4

# Assume openai>=1.0.0
import os

from openai import OpenAI

# Create an OpenAI client with your deepinfra token and endpoint
openai = OpenAI(
    api_key=os.environ["DEEPINFRA_API_KEY"],
    base_url="https://api.deepinfra.com/v1/openai",
)

chat_completion = openai.chat.completions.create(
    model="nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B",
    messages=[{"role": "user", "content": "Hello"}],
)

print(chat_completion.choices[0].message.content)
print(chat_completion.usage.prompt_tokens, chat_completion.usage.completion_tokens)

# Hello! It's nice to meet you. Is there something I can help you with, or would you like to chat?
# 11 25
copy

Featured Model: nvidia/NVIDIA-Nemotron-3-Super-120B-A12B

NVIDIA Nemotron 3 Super is a hybrid Mixture-of-Experts (MoE) model engineered for highest compute efficiency and accuracy in multi-agent applications and specialized agentic systems. It is optimized to run many collaborating agents per application on a single GPU, delivering high accuracy for reasoning, tool use, and instruction following.

Price per 1M input tokens

$0.085

Price per 1M output tokens

$0.40

Release Date

03/10/2026

Context Size

262,144

Quantization

bfloat16

# Assume openai>=1.0.0
import os

from openai import OpenAI

# Create an OpenAI client with your deepinfra token and endpoint
openai = OpenAI(
    api_key=os.environ["DEEPINFRA_API_KEY"],
    base_url="https://api.deepinfra.com/v1/openai",
)

chat_completion = openai.chat.completions.create(
    model="nvidia/NVIDIA-Nemotron-3-Super-120B-A12B",
    messages=[{"role": "user", "content": "Hello"}],
)

print(chat_completion.choices[0].message.content)
print(chat_completion.usage.prompt_tokens, chat_completion.usage.completion_tokens)

# Hello! It's nice to meet you. Is there something I can help you with, or would you like to chat?
# 11 25
copy

Available Nemotron Models

The Nemotron family spans Omni, Nano, Super, and specialized instruct variants, enabling you to balance accuracy, reasoning depth, latency, and cost for your specific workload.

Omni for multimodal reasoning across text, audio, and video
Nano for maximum efficiency and stable inference
Super for multi-agent systems and advanced reasoning
Instruct variants for instruction-following and conversational workloads

Model	Context	$ per 1M input tokens	$ per 1M output tokens	Actions
NVIDIA-Nemotron-3.5-Lightning	256k	$0.06 / $0.03 cached	$0.16	View more
Nemotron-Content-Safety-3.5	128k	$0.20	$0.20	View more
NVIDIA-Nemotron-3-Ultra-550B-A55B	256k	$0.50 / $0.10 cached	$2.20	View more
NVIDIA-Nemotron-3-Super-120B-A12B	256k	$0.085	$0.40	View more

FAQ

How do I integrate Nemotron models into my application?

You can integrate Nemotron models seamlessly using DeepInfra’s OpenAI-compatible API. Just replace your existing base URL with DeepInfra’s endpoint and use your DeepInfra API key—no infrastructure setup required. DeepInfra also supports integration through libraries like openai, litellm, and other SDKs, making it easy to switch or scale your workloads instantly.