nemotron-3-nano-30b-a3b
NVIDIA/🇺🇸 US/chat
NVIDIA Nemotron 3 Nano 30B-A3B is a small language MoE model offering high compute efficiency and accuracy for building specialized agentic AI systems. Fully open weights, datasets, and recipes. Text in/out, up to 256K context.MoreLess
Which id to call
nvidia/nemotron-3-nano-30b-a3bThis 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
262K
tokens
Added
Dec 2025
chat
Capabilities 2/8
Provider rates
What nemotron-3-nano-30b-a3b 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.
OpenAI compatible
Call it in three lines
Change the base url, use your Requesty key, set the model to nvidia/nemotron-3-nano-30b-a3b. 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-nano-30b-a3b", messages=[ {"role": "user", "content": "Explain quantum computing in one paragraph."}, ], ) print(response.choices[0].message.content)
Live from production
NVIDIA on nemotron-3-nano-30b-a3b, measured
What this provider was measured doing on nemotron-3-nano-30b-a3b 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
1.63s
median
p95 wait
5.61s
slowest 5%
Output speed
132/s
median tokens
Cache hit
75.7%
of input tokens
Compare these against the other 1 provider serving nemotron-3-nano-30b-a3b.
Reference
Specs and data terms
What the catalog reports for this deployment, and what the provider does with the traffic.
Released 2025-12-15
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-nano-30b-a3b questions
How much does nemotron-3-nano-30b-a3b cost?
nemotron-3-nano-30b-a3b 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-nano-30b-a3b?
nemotron-3-nano-30b-a3b has a context window of 262K tokens. That's roughly 350 words of input you can fit in a single prompt.
How does nemotron-3-nano-30b-a3b perform on benchmarks?
nemotron-3-nano-30b-a3b scores 91.0% on Math Index, 91.0% on AIME 2025, 79.4% on MMLU Pro. 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-nano-30b-a3b do?
nemotron-3-nano-30b-a3b 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-nano-30b-a3b 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-nano-30b-a3b". The Quickstart above shows Python, JavaScript and cURL snippets.
Can I run nemotron-3-nano-30b-a3b through Requesty?
Yes. nemotron-3-nano-30b-a3b 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-nano-30b-a3b", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.
Call nemotron-3-nano-30b-a3b through one endpoint
One key for this endpoint and 600+ other models. No markup on provider prices, automatic failover, caching built in.