Small models are having a moment. On the heels of the release of a new AI vision model small enough to fit on a smartwatch from MIT spinoff Liquid AI, and a model small enough to run on a smartphone from Google, Nvidia is joining the party today with a new small language model (SLM) of its own, Nemotron-Nano-9B-V2, which attained the highest performance in its class on selected benchmarks and comes with the ability for users to toggle on and off AI “reasoning,” that is, self-checking before outputting an answer. While the 9 billion parameters are larger than some of the multimillion parameter small models VentureBeat has covered recently, Nvidia notes it is a meaningful reduction from its original size of 12 billion parameters and is designed to fit on a single Nvidia A10 GPU. As Oleksii Kuchiaev, Nvidia Director of AI Model Post-Training, said on X in response to a question I submitted to him: “The 12B was pruned to 9B to specifically fit A10 which is a popular GPU choice for deployment. It is also a hybrid model which allows it to process a larger batch size and be up to 6x faster than similar sized transformer models.”

Full report : Nvidia debuts Nemotron-Nano-9B-v2, a hybrid Mamba-Transformer model, saying it achieves comparable or better accuracies than Qwen3-8B on reasoning benchmarks.