Nvidia Nemotron 3.5 Lightning 30B A3B BF16
NVIDIA's Nemotron 3.5 Lightning 30B A3B BF16 is a 30-billion parameter, open-source chat model designed for customization and deployment on NVIDIA hardware. It is built with a hybrid MoE architecture combining Mamba-2, MoE, and Attention components, and supports an exceptionally long context window of up to 1 million tokens.
Input
Output
Context
262K
Max Output
262K
Parameters
31.6B
Technical Specifications
Input Modalities
Output Modalities
Capabilities
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Resources & Links
Estimated GPU requirements for Nvidia Nemotron 3.5 Lightning 30B A3B BF16
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.
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Frequently asked questions about Nvidia Nemotron 3.5 Lightning 30B A3B BF16
Answered from the entry's own fields: context, license, modalities, evidence, serving and the memory to self-host.
Nvidia Nemotron 3.5 Lightning 30B A3B BF16 advertises a context window of 262,144 tokens, with a maximum output of 262,144 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 3.5 Lightning 30B A3B BF16 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 3.5 Lightning 30B A3B BF16 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 3.5 Lightning 30B A3B BF16 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 3.5 Lightning 30B A3B BF16 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 31.1 GB at INT8 for the weights and a default context, from the catalog's 31.6B 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
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