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-5.2-Codex 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_e6747be4 |
| How much it can read and write | Reads up to 400,000 tokens at once, writes up to 128,000 | its own listing |
| Whether it thinks before answering | Always reasons, and cannot be turned off, at xhigh, high, medium, low, medium by default | 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-5.2-Codex 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: 6 prompt tokens.
GPT-5.2-Codex is an upgraded version of GPT-5.1-Codex optimized for software engineering and coding workflows. It is designed for both interactive development sessions and long, independent execution of complex engineering tasks....
Supported parameters
include_reasoningmax_completion_tokensreasoningreasoning_effortresponse_formatseedstructured_outputstool_choicetoolsverbosity
defaults: {"temperature":null,"top_p":null,"frequency_penalty":null}
