nemotron-3-super-120b-a12b
NVIDIA/🇺🇸 US/chat
NVIDIA Nemotron 3 Super is a 120B-parameter open hybrid Mamba-Transformer MoE model activating just 12B parameters, with multi-token prediction for high throughput. 1M token context for long-horizon agent coherence, cross-document reasoning, and multi-step planning. Strong on AIME 2025, TerminalBench, and SWE-Bench Verified. Part of the NVIDIA Nemotron family.MoreLess
Which id to call
nvidia/nemotron-3-super-120b-a12bThis exact deployment on NVIDIA, with no routing and no failover. Send it as the model field.
Input /1M
free
NVIDIA
Output /1M
free
no charge
Context
1.0M
66K output
Added
Mar 2026
chat
Capabilities 2/8
Provider rates
What nemotron-3-super-120b-a12b costs
Provider prices per 1M tokens, updated September 8, 2026.moreless
These are the upstream provider rates. Pay as you go adds 5%, or 0% if you bring your own keys, and there is no per-request fee. Prompt caching and routing change what you pay against these rates, not the rates themselves.
Input /1M
free
Output /1M
free
Cache write /1M
-
Cache read /1M
-
What a workload costs
- 100K input + 10K output
- free
- 1M input + 100K output
- free
- 10M input + 1M output
- free
At the rates above. This endpoint does not offer prompt caching, so repeated context is billed as new input every time.
model=
Which id to call
One base url, https://router.requesty.ai/v1, and one key for every id here.
nvidia/nemotron-3-super-120b-a12bThis exact deployment on NVIDIA, with no routing and no failover. Send it as the model field.
OpenAI compatible
Call it in three lines
Change the base url, use your Requesty key, set the model to any id on the left. Existing OpenAI SDK code needs no other edit.
123456789101112131415from openai import OpenAI client = OpenAI( api_key="YOUR_REQUESTY_API_KEY", base_url="https://router.requesty.ai/v1", ) response = client.chat.completions.create( model="nvidia/nemotron-3-super-120b-a12b", messages=[ {"role": "user", "content": "Explain quantum computing in one paragraph."}, ], ) print(response.choices[0].message.content)
Live from production
NVIDIA on nemotron-3-super-120b-a12b, measured
What this provider was measured doing on nemotron-3-super-120b-a12b across Requesty traffic.moreless
Whole-window figures, because that is the grain published per provider. They cover NVIDIA serving this model in every region it serves it from, so a region-pinned deployment shares them with its siblings. A figure is absent where no qualifying sample exists.
First token
2.63s
median
p95 wait
14.16s
slowest 5%
Output speed
91/s
median tokens
Cache hit
72.3%
of input tokens
Reference
Specs and data terms
What the catalog reports for this deployment, and what the provider does with the traffic.
Released 2026-03-11
Benchmark scores
Benchmarks measure the model, not this endpoint, so they are the same wherever these weights are served.
Artificial Analysis Coding Index: a composite of coding evaluations including LiveCodeBench, SciCode and Terminal-Bench.
Graduate-level physics, chemistry & biology questions designed to resist Googling.
Artificial Analysis Intelligence Index: a composite of multiple evaluations measuring overall model capability.
Scores from official model cards, Artificial Analysis and public leaderboards. They measure specific skills and do not capture every aspect of model quality, so test on your own workload.
Same provider
More from NVIDIA
Newest first, on the same provider and the same key.
Reference
nemotron-3-super-120b-a12b questions
How much does nemotron-3-super-120b-a12b cost?
nemotron-3-super-120b-a12b is priced at free per million input tokens and free per million output tokens when accessed via Requesty. Those are the upstream provider rates: pay as you go adds 5% on top, or 0% if you bring your own provider keys.
What is the context window of nemotron-3-super-120b-a12b?
nemotron-3-super-120b-a12b has a context window of 1.0M tokens, with a maximum output of 66K tokens per response. That's roughly 1,398 words of input you can fit in a single prompt.
How does nemotron-3-super-120b-a12b perform on benchmarks?
nemotron-3-super-120b-a12b scores 80.0% on GPQA Diamond, 67.8% on τ²-Bench, 37.7% on Coding Index. See the full benchmark chart above for results across MMLU Pro, GPQA Diamond, SWE-Bench Verified, HumanEval, MATH, AIME, MMMU, and LiveBench.
What can nemotron-3-super-120b-a12b do?
nemotron-3-super-120b-a12b supports tool calling, extended reasoning. You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use nemotron-3-super-120b-a12b with the OpenAI SDK?
Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "nvidia/nemotron-3-super-120b-a12b". The Quickstart above shows Python, JavaScript and cURL snippets.
Can I run nemotron-3-super-120b-a12b through Requesty?
Yes. nemotron-3-super-120b-a12b runs through Requesty's OpenAI-compatible API, served from NVIDIA. You do not host the model yourself: point base_url at Requesty, set the model to "nvidia/nemotron-3-super-120b-a12b", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.
Call nemotron-3-super-120b-a12b through one endpoint
One key for this endpoint and 600+ other models. No markup on provider prices, automatic failover, caching built in.