Llama 3.1 Nemotron Nano 8B V1
NVIDIA's Llama 3.1 Nemotron Nano 8B V 1 is a large language model exceling at reasoning, text generation, and function calling, with a notable context length of 128K. It is well-suited for developers designing AI agent systems, chatbots, and other AI-powered applications, offering a balance of model accuracy and efficiency. The model's multi-phase post-training process, including supervised fine-tuning and reinforcement learning stages, enhances its capabilities.
Input
Output
Context
131K
Max Output
2K
Parameters
8B
Technical Specifications
Input Modalities
Output Modalities
Capabilities
Loading capabilities…
Resources & Links
Estimated GPU requirements for Llama 3.1 Nemotron Nano 8B V1
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 Llama 3.1 Nemotron Nano 8B V1
Answered from the entry's own fields: context, license, modalities, evidence, serving and the memory to self-host.
Llama 3.1 Nemotron Nano 8B V1 advertises a context window of 131,072 tokens, with a maximum output of 2,048 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. Llama 3.1 Nemotron Nano 8B V1 is an open-weight model released under the Other license, so the weights can be downloaded and self-hosted within that license's terms.
Llama 3.1 Nemotron Nano 8B V1 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 Llama 3.1 Nemotron Nano 8B V1 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; Llama 3.1 Nemotron Nano 8B V1 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 8.2 GB at INT8 for the weights and a default context, from the catalog's 8B 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: Aug 28, 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.