Why high: an exact fingerprint shared with 40 models that declare the same family, without a second signal of a different kind yet.
OpenAI: GPT-3.5 Turbo (older v0613) is OpenAI's model. Its measured tokenizer sits with the GPT group, which is evidence that it builds on the GPT tokenizer. Tokenizer reuse is normal engineering, open vocabularies travel between labs, and this says nothing against OpenAI'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 40 other models | tk_d1411c9d |
| How its API is set up | A combination of settings no other listing in the catalogue uses | api_fa93c9dc |
| How much it can read and write | Reads up to 4,095 tokens at onceOpenRouter's listing shows 3,685 output tokens, which is 90% of the context window, the figure it carries where the provider declares no maximum. | its own listing |
| Who served our requests | Azure | we measured it, 3 September 2026 |
Click a row to open the full comparison.
We sent OpenAI: GPT-3.5 Turbo (older v0613) 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: 7 prompt tokens.
GPT-3.5 Turbo is OpenAI's fastest model. It can understand and generate natural language or code, and is optimized for chat and traditional completion tasks. Training data up to Sep 2021.
Supported parameters
frequency_penaltylogit_biaslogprobsmax_completion_tokenspresence_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_logprobstop_p
defaults: {}
