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NVIDIA Nemotron 3 Super 120B A12B

NVIDIA Nemotron 3 Super 120B A12B is a verified current AI model with official specifications, pricing or access details, capabilities, best use cases, strengths and limitations.

Open-Weight Reasoning ModelText Freemium
In plain English

What is this model and why does it matter?

NVIDIA Nemotron 3 Super 120B A12B is a 120B-total, 12B-active open-weight reasoning model with up to 1M context, optimized for agents, RAG, tool use and high-volume workloads.

AgentsRAGIT automationLong-context reasoningPrivate deployments
Model overview

NVIDIA Nemotron 3 Super 120B A12B: features, use cases and important details

NVIDIA Nemotron 3 Super 120B A12B is a current AI model verified from first-party NVIDIA sources.

NVIDIA Nemotron 3 Super 120B A12B verified specifications

NVIDIA Nemotron 3 Super 120B A12B is a 120B-total, 12B-active open-weight reasoning model with up to 1M context, optimized for agents, RAG, tool use and high-volume workloads. Its verified context or usage limit is Up to 1000000 tokens, with Deployment configurable; official examples use up to 32000 generated tokens maximum output.

NVIDIA Nemotron 3 Super 120B A12B pricing and access

NVIDIA provides a free prototype NIM endpoint and downloadable weights. Production partner/self-hosted cost depends on the selected infrastructure rather than a single published token price.

NVIDIA Nemotron 3 Super 120B A12B best uses

Agents, RAG, IT automation, Long-context reasoning, Private deployments.

NVIDIA Nemotron 3 Super 120B A12B limitations

Default self-host configurations may use shorter context, Large GPU requirements for full-scale deployment, Requires use-case testing.

Get started

How to use this model

  1. Generate an NVIDIA API key for the prototype or download the weights.
  2. Call nvidia/nemotron-3-super-120b-a12b.
  3. Enable or disable reasoning through the chat template.
  4. Connect tool parsing where required.
  5. Benchmark 256K versus 1M deployment memory needs.
Copy and try

Example prompts

  • Automate triage for these IT tickets.
  • Reason across this long enterprise knowledge base.
  • Use tools to solve this multi-step operational task.
Capabilities

What it can do

  • 120B total / 12B active
  • 1M context
  • Configurable reasoning
  • Tool use
  • Structured outputs
  • Downloadable weights
Best for

Practical use cases

  • Enterprise agents
  • RAG
  • IT automation
  • Private assistants
  • Long-context analysis
Pricing

What does it cost?

NVIDIA provides a free prototype NIM endpoint and downloadable weights. Production partner/self-hosted cost depends on the selected infrastructure rather than a single published token price.

InputFree prototype; production infrastructure dependent
OutputFree prototype; production infrastructure dependent
Simple summaryA free prototype endpoint is available; production cost depends on partner or self-hosted GPU infrastructure.

What stands out

  • 65M-class recent NIM usage signal
  • 1M context
  • Downloadable weights
  • Commercial use
  • Free prototype endpoint

Things to consider

  • Large self-hosting footprint
  • Custom NVIDIA license rather than standard OSI license
  • Text only
Limitations

Important restrictions and trade-offs

  • Default self-host configurations may use shorter context
  • Large GPU requirements for full-scale deployment
  • Requires use-case testing
SimplifyAITools verdict

Our editorial take

One of NVIDIA’s most-used current Nemotron models and a strong high-demand addition for open-weight enterprise agent searches.

References

Primary sources

  1. Open source 1 ↗
  2. Open source 2 ↗
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