NVIDIA: Nemotron 3 Nano 30B A3B

NVIDIA Nemotron 3 Nano 30B A3B is a small language model built by NVIDIA as part of its Nemotron family. The name reflects its architecture: a mixture-of-experts design with roughly 30 billion parameters in total and about 3 billion active per token, which NVIDIA describes as delivering high compute efficiency and accuracy. It is a text model aimed at developers building specialized agentic AI systems, and it was released by the provider on 14 December 2025.

The model takes text in and returns text out. Its context window is 262,144 tokens, with a maximum output of 235,929 tokens, so it can accept very long inputs and produce long completions in a single request. Alongside plain generation, the supported parameters suggest reasoning and structured output as first class features: reasoning and include_reasoning are both accepted, as are response_format, structured_outputs and tools. Sampling and decoding controls include temperature, top_p, top_k, repetition_penalty, frequency_penalty, presence_penalty, stop, seed and logit_bias, plus logprobs and top_logprobs for inspecting token level probabilities.

Those capabilities point to a few practical workloads. The large context window suits long document processing, such as summarization, extraction and question answering over sizable codebases or report collections, without aggressive chunking. The agentic positioning, combined with tool calling and structured outputs, fits pipelines where the model decides which tools to invoke and returns machine readable results, for example data enrichment, retrieval orchestration or multi step automation. The reasoning controls are useful for tasks where you want the model's intermediate thinking separated from its final answer, such as analysis, planning or debugging. Because it is a small, efficiency focused model, it also fits high volume text transformation jobs where throughput matters more than peak capability.

You call it through api14's OpenAI-compatible API using the model id "nvidia/nemotron-3-nano-30b-a3b". Because the endpoint follows the OpenAI schema, standard chat completions style requests work, and you can pass any of the parameters listed above in the request body, including tools and tool_choice for function calling, response_format for structured responses, and max_tokens to cap output length. Streaming and logging options behave as they do for other models on the gateway.

It is a text only model. It does not accept image or audio input, so multimodal tasks require a different model, and the provider description positions it for specialized agentic systems rather than as a general flagship. If a workload needs vision, other input modalities, or a larger model's broader knowledge, consider alternatives; for long context, reasoning heavy or tool driven text pipelines, this model's combination of a 262,144 token window, tool support and efficient MoE architecture is the reason to pick it.