Most major AI model releases arrive with big boasts about speed, intelligence or capability. GPT-5.1 is different. Rather than stretching the ceiling on reasoning or performance, OpenAI’s new flagship model is pitched around something a little more pragmatic: control, adaptability, and predictable behaviour.
It’s the first release where OpenAI openly reorganises its model lineup around two distinct operating modes — Instant and Thinking — and lets the system route between them automatically. The change alludes to where large-scale AI development is heading: performance still matters, of course, but predictable, steerable behaviour is a real priority.
On that note, OpenAI is also taking a leaf out of Anthropic’s book by letting users customize ChatGPT’s tone and personality — “Professional,” “Efficient,” “Nerdy,” “Cynical,” and others — formalising something users previously hacked together through long prompt templates.
And under the hood, GPT-5.1 adjusts its reasoning depth based on task complexity, aiming to solve simple queries quickly while sticking with harder ones longer.
For most people, those changes manifest themselves as a smoother ChatGPT. For developers, the story is broader — because GPT-5.1 arrives with a parallel release built specifically for them.
Alongside the consumer-grade rollout, OpenAI published GPT-5.1 for Developers, a version that exposes the model’s new behaviour in a form meant for production systems.
And early signs suggest those developer-oriented changes matter in practice. On Terminal-Bench 2.0 — a benchmark measuring how well models operate in command-line environments — GPT-5.1 Codex currently leads with about 58% accuracy, ahead of both GPT-5 and Claude Sonnet.
The number itself is modest, but it points to improvements where real system interaction, structured outputs, and multi-step tool use matter more than raw reasoning scores.
One of the key structural changes is this: developers can now opt out of deeper reasoning altogether by setting reasoning_effort to “none,” or let the system decide how much thinking the model should do. It’s a small switch with practical impact – forcing shallow reasoning makes responses faster, cheaper, and more predictable, and removes the need for brittle prompt tricks to keep the model terse. In other words, shallow and deep tasks no longer require separate models; the API can arbitrate.
OpenAI positions the developer-grade release as more than an API binding – a model tuned to “balance intelligence and speed for a wide range of agentic and coding tasks.” That balance, the company says, comes partly from GPT-5.1’s adaptive reasoning behaviour.
“GPT-5.1 dynamically adapts how much time it spends thinking based on the complexity of the task, making the model significantly faster and more token-efficient on simpler everyday tasks,” the company wrote in a blog post.
Elsewhere, OpenAI is adding new tools aimed at smoothing real development workflows. GPT-5.1 introduces an apply_patch tool for making code edits without the usual JSON-escaping friction, and a new `shell` tool that lets the model propose commands intended to run on a local machine. They’re small additions, but they push the model further toward reliable code manipulation and practical system interaction.
Beyond the toolset, OpenAI also highlights changes inside the model itself: more dependable structured outputs, improved function calling, and steadier multi-step tool use. In OpenAI’s telling, these upgrades are meant to make agent-style applications less fragile — the kind of environments where consistency usually matters more than clever one-offs.
GPT-5.1 might not dazzle, but its focus on everyday production pain points is notable. It targets quieter failure modes that break real systems, such as unpredictable behaviour, brittle tool calls, and workflows that collapse when phrasing changes.
In that sense, GPT-5.1 is perhaps more about making large models behave like dependable infrastructure.
