Why high: an exact fingerprint shared with 8 models that declare the same family, without a second signal of a different kind yet.
Perplexity: Sonar Pro is Perplexity's model. Its measured tokenizer sits with the Llama3 group, which is evidence that it builds on the Llama3 tokenizer. Tokenizer reuse is normal engineering, open vocabularies travel between labs, and this says nothing against Perplexity'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 8 other models | tk_6588ed5b |
| How its API is set up | A combination of settings no other listing in the catalogue uses | api_25d972de |
| How much it can read and write | Reads up to 200,000 tokens at once, writes up to 8,000 | its own listing |
| Who served our requests | Perplexity | we measured it, 3 September 2026 |
Click a row to open the full comparison.
We sent Perplexity: Sonar Pro 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: 0 prompt tokens.
Note: Sonar Pro pricing includes Perplexity search pricing. See [details here](https://docs.perplexity.ai/guides/pricing#detailed-pricing-breakdown-for-sonar-reasoning-pro-and-sonar-pro) For enterprises seeking more advanced capabilities, the Sonar Pro API can handle in-depth, multi-step queries with added extensibilit…
Supported parameters
frequency_penaltymax_tokenspresence_penaltytemperaturetop_ktop_pweb_search_options
defaults: {}
