Why high: an exact fingerprint shared with 21 models that declare the same family, without a second signal of a different kind yet.
NVIDIA: Nemotron 3 Ultra 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 | Counts every one of the 50 test strings exactly like 21 other models | tk_0da8a999 |
| How its API is set up | A combination of settings no other listing in the catalogue uses | api_65d2ace2 |
| How much it can read and write | Reads up to 262,144 tokens at once, writes up to 16,384 | its own listing |
| Whether it thinks before answering | Reasons when asked to, at high, medium, high by default | its own listing |
| Who served our requests | BaseTen | we measured it, 5 October 2026 |
| Measured twice | The 5 October 2026 reading agreed with the 3 September 2026 reading on every one of the 50 strings clean in both: the tokenizer behind this name held. | 50/50 agree |
Click a row to open the full comparison.
We sent NVIDIA: Nemotron 3 Ultra 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: 17 prompt tokens.
NVIDIA Nemotron 3 Ultra is an open frontier-reasoning and orchestration model from NVIDIA, with 55B active parameters out of 550B total (MoE). Built on a hybrid Transformer-Mamba mixture-of-experts architecture, it...
Supported parameters
frequency_penaltyinclude_reasoninglogit_biasmax_tokensmin_ppresence_penaltyreasoningreasoning_effortrepetition_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_ktop_p
defaults: {"temperature":1,"top_p":0.95,"top_k":null,"frequency_penalty":null,"presence_penalty":null,"repetition_penalty":null}
