NVIDIA Nemotron 3 Nano 4B
NVIDIA develops the Nvidia Nemotron 3 Nano 4B BF 16, a small language model designed for unified reasoning and non-reasoning tasks, with capabilities including function calling, JSON mode, streaming, and text generation. It is particularly effective in tasks that require generating reasoning traces, which can be controlled via system prompts, and achieves notable scores, such as 91.1 on RULER (128k) and 88 on IFEval-Instruction.
Input
Output
Context
262K
Max Output
16K
Parameters
4B
Technical Specifications
Input Modalities
Output Modalities
Capabilities
Loading capabilities…
Resources & Links
Estimated GPU requirements for NVIDIA Nemotron 3 Nano 4B
Estimates based on INT8 quantization at up to 32K context. A count above one assumes tensor parallelism across the cards. Actual requirements vary by framework and configuration.
More models by NVIDIA
The creator's other models in the catalog, with their context, size and license where published.
Compare it, or keep browsing
Put this model beside its alternatives on the same evidence, or go back to the full catalog.
Frequently asked questions about NVIDIA Nemotron 3 Nano 4B
Answered from the entry's own fields: context, license, modalities, evidence, serving and the memory to self-host.
NVIDIA Nemotron 3 Nano 4B advertises a context window of 262,144 tokens, with a maximum output of 16,384 tokens in a single response. The figure is the creator's published maximum; a given host may serve less, and the gateway routes on what each host actually serves.
Yes. NVIDIA Nemotron 3 Nano 4B is an open-weight model released under the Other license, so the weights can be downloaded and self-hosted within that license's terms.
NVIDIA Nemotron 3 Nano 4B accepts Text and produces Text. The capabilities card on this page lists which API features each deployment honours, such as function calling and structured output, with the source each was checked against.
No published benchmark result for NVIDIA Nemotron 3 Nano 4B is in the catalog yet, so the model is shown as unmeasured. It is not ranked or estimated; the router treats it as unknown for every task until a suite measures it.
Not on the managed pool today; NVIDIA Nemotron 3 Nano 4B is listed for reference and comparison. Connect your own provider key or endpoint that serves it and the gateway runs it on your account, with routing decisions recorded the same way.
About 4.3 GB at INT8 for the weights and a default context, from the catalog's 4B parameter count; FP16 needs roughly twice that, and long contexts or many concurrent requests add KV cache on top. The GPU section on this page lists cards that hold it, and the capacity planner sizes it for your context length and traffic.
Fields collected from public registries, host APIs and benchmark publishers, each tagged with its source.
Last updated: Sep 22, 2026
Put intelligence in the middle.
One gateway in front of every model, with your policies applied and every decision on record. Start with $5 of credit and 5,000 routing decisions a month, no card required.