Friday, 14th November 2025
GPT-5.1 Instant and GPT-5.1 Thinking System Card Addendum. I was confused about whether the new "adaptive thinking" feature of GPT-5.1 meant they were moving away from the "router" mechanism where GPT-5 in ChatGPT automatically selected a model for you.
This page addresses that, emphasis mine:
GPT‑5.1 Instant is more conversational than our earlier chat model, with improved instruction following and an adaptive reasoning capability that lets it decide when to think before responding. GPT‑5.1 Thinking adapts thinking time more precisely to each question. GPT‑5.1 Auto will continue to route each query to the model best suited for it, so that in most cases, the user does not need to choose a model at all.
So GPT‑5.1 Instant can decide when to think before responding, GPT-5.1 Thinking can decide how hard to think, and GPT-5.1 Auto (not a model you can use via the API) can decide which out of Instant and Thinking a prompt should be routed to.
If anything this feels more confusing than the GPT-5 routing situation!
The system card addendum PDF itself is somewhat frustrating: it shows results on an internal benchmark called "Production Benchmarks", also mentioned in the GPT-5 system card, but with vanishingly little detail about what that tests beyond high level category names like "personal data", "extremism" or "mental health" and "emotional reliance" - those last two both listed as "New evaluations, as introduced in the GPT-5 update on sensitive conversations" - a PDF dated October 27th that I had previously missed.
That document describes the two new categories like so:
- Emotional Reliance not_unsafe - tests that the model does not produce disallowed content under our policies related to unhealthy emotional dependence or attachment to ChatGPT
- Mental Health not_unsafe - tests that the model does not produce disallowed content under our policies in situations where there are signs that a user may be experiencing isolated delusions, psychosis, or mania
So these are the ChatGPT Psychosis benchmarks!
parakeet-mlx. Neat MLX project by Senstella bringing NVIDIA's Parakeet ASR (Automatic Speech Recognition, like Whisper) model to to Apple's MLX framework.
It's packaged as a Python CLI tool, so you can run it like this:
uvx parakeet-mlx default_tc.mp3
The first time I ran this it downloaded a 2.5GB model file.
Once that was fetched it took 53 seconds to transcribe a 65MB 1hr 1m 28s podcast episode (this one) and produced this default_tc.srt file with a timestamped transcript of the audio I fed into it. The quality appears to be very high.