OpenAI's Ultrafast tier leaves teams to measure GPT-6.1 Sol's speedup themselves

Putting the speed choice on the request is good design ^[7]. The routing rule lives in the code that already knows whether a person is waiting. Each call site can move to the faster tier, or back, on its own.

Speed is the open variable. OpenAI positions Ultrafast as the fastest option for GPT-6.1 Sol ^[6]. For now the adjective is the whole specification: the dev.to writeup says OpenAI's documentation does not include a response-time figure, and it warns against promising a specific latency improvement ^[3].

For the premium to pay back, a person has to be waiting on the reply. The wait also has to be mostly model time. A request that spends its seconds in retrieval, tool calls or a slow client gains little from a faster serving tier. It still pays the 6x rate ^[2].

This is the comparison I would run before moving any call site:

1. Sample real prompts from each call site where someone waits on the output. 2. Replay each prompt on Standard and on Ultrafast, recording time to first token and total completion time. 3. Divide the extra spend, five Standard calls' worth per request ^[12], by the seconds saved.

Call sites with a low cost per second saved move to Ultrafast. The rest stay on Standard.

The writeup's own candidates make a reasonable first sample. It lists live support-reply drafting, code assistance in Codex, triage of short incoming requests, and drafts that staff review before approval ^[4]. Background jobs and batch work are its examples of tasks that may not justify the extra cost ^[10]. It is also explicit that the tier addresses speed, and that its examples are not a promise of better output or of less review ^[5].

Codex and Work spend needs its own forecast, built from the credit rates. The writeup advises checking the rules on each account before carrying the API multiplier across products ^[11].