What is GPT-5.1 in simple terms?

GPT-5.1 is an updated version of OpenAI’s GPT-5 model that powers both ChatGPT and the API. It adds new Instant and Thinking modes, adaptive reasoning and richer personality controls while keeping similar overall capabilities and price to GPT-5.

How does GPT-5.1 help developers ship code faster?

GPT-5.1 adjusts how much reasoning it does per request, so easy tasks finish with fewer tokens and lower latency while harder problems still get extra thinking time. New tools like the apply_patch code editor, a shell tool and 24-hour prompt caching make it easier to build agents that can edit, run and iterate on code with fewer manual steps.

Is GPT-5.1 available in the OpenAI API and how do I use it?

Yes. In the OpenAI platform you can call GPT-5.1 with model names like gpt-5.1 or gpt-5.1-chat-latest, and choose reasoning_effort levels from none to high depending on your latency and quality needs. For long-running coding work, you can also use gpt-5.1-codex, gpt-5.1-codex-mini or GPT-5.1-Codex-Max in Codex environments.

Does GPT-5.1 replace GPT-5 right away?

OpenAI keeps GPT-5 available for now but is clearly steering new features and investments toward GPT-5.1 and Codex-based models. Teams can migrate gradually by testing GPT-5.1 on specific endpoints or workflows, comparing speed, cost and quality before making it the default across their stack.

OpenAI rolls out GPT-5.1 to help developers ship faster

Updated on November 28, 2025 6 minutes read

Modern open office desk with laptop showing colorful code and glowing AI diagram, illustrating GPT-5.1 speeding up software development.

OpenAI has begun rolling out GPT-5.1, an update to the GPT-5 series that aims to make ChatGPT and the API faster, more conversational and better at coding-heavy tasks. On 12 November 2025 the company enabled GPT-5.1 Instant and GPT-5.1 Thinking in ChatGPT, positioning them as upgrades to the GPT-5 model introduced in August 2025.

A day later, on 13 November 2025, OpenAI released GPT-5.1 on its API platform along with new tooling for agentic workflows, including extended prompt caching, an apply_patch code-editing tool and a shell tool.

GPT-5.1 dynamically adjusts how much reasoning it does per request, adds a none (no reasoning) mode for latency-sensitive workloads, and keeps pricing and rate limits aligned with GPT-5.

For developers, students and teams in Canada, the pitch is simple: GPT-5.1 should plug into existing GPT-5 workflows while cutting response times and token bills, especially for coding tasks, without forcing a full rewrite of tools or curricula.

What happened

On 12 November 2025, OpenAI announced GPT-5.1 as a smarter, more conversational ChatGPT and started rolling it out first to paid ChatGPT users.

In ChatGPT, the release introduces two variants: GPT-5.1 Instant, a faster default mode tuned to feel warmer and follow instructions more reliably, and GPT-5.1 Thinking, a higher-end reasoning mode that spends more time on complex problems.

OpenAI also expanded personality presets so users can select tones such as Default, Professional, Friendly or more playful styles, and it is testing more fine-grained controls for tone and style in the settings UI.

On 13 November 2025, GPT-5.1 arrived in the API as the next model in the GPT-5 series, designed to balance intelligence and speed for agentic and coding workloads.

The API release adds adaptive reasoning that lets the model spend fewer tokens on easy tasks and more on difficult ones, a reasoning_effort parameter that supports a none mode by default, and extended prompt caching that keeps context hot for up to 24 hours.

Developers also gain two new tools in the Responses API: apply_patch, which emits structured patches to create or edit files, and a shell tool that lets the model propose terminal commands for a controlled plan-execute loop.

In parallel, OpenAI introduced GPT-5.1-Codex-Max on 19 November 2025 for project-scale coding inside Codex, and GPT-5.1 is now the engine behind a free ChatGPT for Teachers programme that gives verified US K-12 educators unlimited access through June 2027.

Together these moves signal that GPT-5.1 is not just a minor model bump; it is the platform OpenAI wants developers and educators to build on for the next wave of AI-assisted work.

Why it matters

For teams that already ship with AI, GPT-5.1 aims to reduce latency and cost without forcing you to choose between fast but shallow and “slow but smart”. Adaptive reasoning means simple tasks can complete with far fewer tokens and seconds, while hard tasks still benefit from extended thinking.

In OpenAI’s partner benchmarks, Balyasny Asset Management reports that GPT-5.1 outperformed both GPT-4.1 and GPT-5 in its evaluation suite while running roughly two to three times faster than GPT-5 and using about half as many tokens as leading competitors on tool-heavy workloads.

AI insurance provider Pace says its agents run about 50% faster on GPT-5.1 while exceeding GPT-5’s accuracy, and infrastructure startup Sierra measured a 20% improvement in low-latency tool-calling performance when using the new none mode compared with GPT-5 at minimal reasoning.

On coding benchmarks such as SWE-bench Verified, GPT-5.1 reaches 76.3% accuracy while using fewer thinking tokens on easy tasks, which matters if you are pushing frequent diffs through an AI agent or IDE extension.

For learners at Code Labs Academy, those gains translate into more responsive code reviews, faster iterations on projects and a better chance that an assistant can follow multi-step instructions when you are debugging or refactoring. For Canadian teams building internal tools, the same features offer a practical route to experiment with agents and code-editing bots without exploding cloud spend.

Because GPT-5.1 also underpins ChatGPT for Teachers, with unlimited GPT-5.1 Auto messaging for verified educators, the model is becoming a baseline tool in classrooms, another reason bootcamp students should expect to work alongside it rather than around it.

Key numbers

12 November 2025 - GPT-5.1 Instant and GPT-5.1 Thinking begin rolling out in ChatGPT as upgrades to GPT-5.
13 November 2025 - GPT-5.1 becomes available in the API (gpt-5.1 and gpt-5.1-chat-latest) with pricing and rate limits matching GPT-5.
Up to 24 hours - extended prompt caching window for GPT-5.1, with cached input tokens priced at 10% of standard input cost.
76.3% - GPT-5.1’s score on SWE-bench Verified, a 500-problem benchmark where models must generate code patches that actually fix issues.
2-3x faster - speed-up Balyasny Asset Management reports for GPT-5.1 versus GPT-5 in its dynamic evaluation suite, while using about half as many tokens as leading competitors.
50% faster - Pace’s reported speed-up for its agents when switching from GPT-5 to GPT-5.1, at higher accuracy.
20% improvement - Sierra’s measured boost in low-latency tool-calling performance for GPT-5.1 with reasoning_effort = none versus GPT-5 at minimal reasoning.
77.9% vs 73.7% - SWE-bench Verified scores for GPT-5.1-Codex-Max versus GPT-5.1-Codex at extra-high reasoning effort, with Codex-Max using 30% fewer thinking tokens at matched performance.
Through June 2027 - ChatGPT for Teachers offers free, unlimited GPT-5.1 Auto messaging for verified US K-12 educators.
~800 million - weekly ChatGPT users OpenAI cites when explaining why teachers are among its most active adopters.

Context

GPT-5 arrived in August 2025 as OpenAI’s next-generation model, but early reaction was mixed, with some users complaining about tone and perceived regressions compared with earlier releases; the company even re-enabled GPT-4o for a period to address those concerns.

GPT-5.1 is framed as a corrective: on the ChatGPT side it focuses on conversational warmth, clearer instruction following and user-controllable personality presets, while on the API side it emphasizes predictable reasoning behaviour and concrete savings on time and tokens.

OpenAI’s documentation now positions GPT-5.1 as its flagship model for coding and agentic tasks, with gpt-5.1-codex and gpt-5.1-codex-mini specialising in long-running coding workloads and GPT-5.1-Codex-Max handling project-scale refactors over millions of tokens.

In a market where rivals such as Anthropic’s Claude and Google’s Gemini are also pivoting into developer tooling, GPT-5.1’s mix of reasoning modes, caching and tools is OpenAI’s argument that its stack remains a default choice for code agents, IDE integrations and AI-assisted learning platforms. This piece focuses on those launch details rather than comparing every model family.

What’s next

OpenAI has signalled that GPT-5 will remain available for now, but future investments will concentrate on GPT-5.1 and successors, with more capable agentic and coding models promised in the coming weeks and months.

On the Codex side, GPT-5.1-Codex-Max is already the default model in Codex surfaces, and internal telemetry at OpenAI suggests that 95% of its engineers use Codex weekly and ship around 70% more pull requests since adopting it, an indication of where day-to-day engineering workflows may be heading.

For developers, the practical checklist looks straightforward: experiment with GPT-5.1 in non-critical environments, tune reasoning_effort per endpoint (for example none on chat UIs and medium or high on refactors), and adopt extended caching where conversations or projects span multiple sessions.

For learners at Code Labs Academy, GPT-5.1 is a reason to practise building with AI-native workflows: pair-programming on portfolio projects, using apply_patch and shell-style tools in safe sandboxes, and learning how to review and test AI-generated code rather than copy-pasting snippets blindly.

How to go deeper

To go further with GPT-5.1 and adjacent skills:

Explore the full-stack Web Development Bootcamp to practise building end-to-end applications that integrate GPT-5.1 via APIs, frontends and deployment pipelines.

Dig into the Data Science and machine learning bootcamp if you want to understand how evaluation suites like SWE-bench and adaptive reasoning techniques work under the hood.

Strengthen your security skills in the Cybersecurity Bootcamp and learn how to review, test and harden AI-generated code before it goes anywhere near production.