Why high: an exact fingerprint shared with 21 models that declare the same family, without a second signal of a different kind yet.
Mistral: Mixtral 8x22B Instruct is Mistral AI'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 Mistral AI'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_d3c5f5f6 |
| How much it can read and write | Reads up to 65,536 tokens at once, writes up to 52,428 | its own listing |
| Who served our requests | Mistral | we measured it, 3 September 2026 |
Click a row to open the full comparison.
We sent Mistral: Mixtral 8x22B Instruct 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: 15 prompt tokens.
Mistral's official instruct fine-tuned version of [Mixtral 8x22B](/models/mistralai/mixtral-8x22b). It uses 39B active parameters out of 141B, offering unparalleled cost efficiency for its size. Its strengths include: - strong math, coding,...
Supported parameters
frequency_penaltymax_tokenspresence_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_p
defaults: {"temperature":0.3}
