LLM Reference
Fireworks AI

Using Nemotron 3 Super-120B-A12B on Fireworks AI

Implementation guide · Nemotron 3 · NVIDIA AI

ProvisionedOpen Weights

Fireworks AI exposes Nemotron 3 Super-120B-A12B through model ID accounts/fireworks/models/nvidia-nemotron-3-super-120b-a12b-nvfp4. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.

Last refreshed 2026-06-01. Next refresh: weekly.

Quick Start

  1. 1
    Create an account at Fireworks AI and generate an API key.
  2. 2
    Use the Fireworks AI SDK or REST API to call accounts/fireworks/models/nvidia-nemotron-3-super-120b-a12b-nvfp4 — see the documentation for request format.

Code Examples

Install
pip install openai
API key
FIREWORKS_API_KEY
Model ID
accounts/fireworks/models/nvidia-nemotron-3-super-120b-a12b-nvfp4

Fireworks model IDs use "accounts/fireworks/models/{model-name}" format, e.g. "accounts/fireworks/models/llama4-scout-instruct-basic" or "accounts/fireworks/models/deepseek-r1".

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["FIREWORKS_API_KEY"],
    base_url="https://api.fireworks.ai/inference/v1"
)
response = client.chat.completions.create(
    model="accounts/fireworks/models/nvidia-nemotron-3-super-120b-a12b-nvfp4",
    messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)

Pricing on Fireworks AI

Capabilities

Structured Outputs

About Nemotron 3 Super-120B-A12B

NVIDIA Nemotron 3 Super-120B-A12B is a 120B total / 12B active hybrid Latent MoE model with interleaved Mamba-2 and MoE layers for agentic, reasoning, and conversational tasks. Fireworks lists the NVFP4 variant for on-demand deployment with 262k context.

Model Specs

Released2026-03-11
Parameters120B
Context1.05m
ArchitectureDecoder Only

Provider

Fireworks AI
Fireworks AI

San Mateo, California, United States