Why high: one template-boundary shift from a group whose members all declare the same family.
NVIDIA: Nemotron 3 Nano Omni (free) is NVIDIA's model. Its measured tokenizer sits with the Mistral group, which is evidence that it builds on the Mistral tokenizer. Tokenizer reuse is normal engineering, open vocabularies travel between labs, and this says nothing against NVIDIA's authorship of the model itself.
| We checked | What we found | Where it came from |
|---|---|---|
| How it counts tokens | Counted cleanly, and no other model in the catalogue counts the same way | tk_e0b4c23e |
| How its API is set up | A combination of settings no other listing in the catalogue uses | api_e7d911d8 |
| How much it can read and write | Reads up to 256,000 tokens at once, writes up to 65,536 | its own listing |
| Whether it thinks before answering | Reasons when asked to | its own listing |
| Who served our requests | Nvidia | we measured it, 21 August 2026 |
Click a row to open the full comparison.
We sent NVIDIA: Nemotron 3 Nano Omni (free) fifty short pieces of text and recorded what each one cost it in tokens. The bars below are those costs. Two models built on the same tokenizer produce the same bars; a model built on a different one produces a different set, which is what makes this a fingerprint.
Overhead subtracted: 16 prompt tokens.
NVIDIA Nemotron™ 3 Nano Omni is a 30B-A3B open multimodal model designed to function as a perception and context sub-agent in enterprise agent systems. It accepts text, image, video, and...
Supported parameters
include_reasoningmax_tokensreasoningseedtemperaturetool_choicetoolstop_p
defaults: {"temperature":0.6,"top_p":0.95,"top_k":null,"frequency_penalty":null,"presence_penalty":null,"repetition_penalty":null}
