Why high: an exact fingerprint shared with 2 models that declare the same family, without a second signal of a different kind yet.
Venice: Uncensored is Cognitivecomputations'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 Cognitivecomputations'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 2 other models | tk_ddc193e9 |
| How its API is set up | A combination of settings no other listing in the catalogue uses | api_b38ad3f1 |
| How much it can read and write | Reads up to 128,000 tokens at once, writes up to 8,192 | its own listing |
| Who served our requests | Venice | we measured it, 21 August 2026 |
Click a row to open the full comparison.
We sent Venice: Uncensored 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: 557 prompt tokens.
Venice Uncensored Dolphin Mistral 24B Venice Edition is a fine-tuned variant of Mistral-Small-24B-Instruct-2501, developed by dphn.ai in collaboration with Venice.ai. This model is designed as an “uncensored” instruct-tuned LLM, preserving...
Supported parameters
frequency_penaltymax_tokenspresence_penaltyresponse_formatstoptemperaturetop_ktop_p
defaults: {}
