OpenAI has launched GPT-5.1 as the following iteration within the GPT-5 household, with 2 core variants, GPT-5.1 Prompt and GPT-5.1 Considering. The replace focuses on 3 axes, adaptive reasoning habits, clearer explanations, and stronger management over tone and security.
Mannequin Lineup And Positioning
GPT-5.1 Prompt is the default conversational mannequin in ChatGPT. OpenAI describes it as probably the most used mannequin, with a hotter default tone and improved instruction following. GPT-5.1 Considering is the superior reasoning mannequin. It exposes specific considering time and now adjusts that point extra exactly to the query. GPT-5.1 Auto continues to route queries between these variants so most finish customers don’t want to pick out fashions manually.
GPT-5.1 Prompt, Adaptive Reasoning For On a regular basis Use
GPT-5.1 Prompt retains latency low for typical chat use whereas including adaptive reasoning. For easy prompts, the mannequin responds shortly with a shallow inner move. For harder prompts resembling multi step math or coding issues, it chooses to spend extra inner compute earlier than answering. This habits yields greater scores on evaluations like AIME 2025 and Codeforces relative to earlier GPT-5 Prompt variations, whereas staying responsive for informal use.
Instruction following is one other specific goal. In OpenAI’s examples, GPT-5.1 Prompt is extra dependable on constraints resembling ‘all the time reply with 6 phrases’ and maintains that constraint throughout turns. That is related while you construct instruments that depend on strict codecs or brief pure language responses, for instance structured outputs, message templates, or chained instruments that anticipate bounded size.
The mixture of adaptive reasoning and stricter instruction adherence makes GPT-5.1 Prompt a extra predictable entrance finish for a lot of agent workflows the place most calls are easy, however a tail of calls require deeper reasoning.
GPT-5.1 Considering, Dynamic Compute Allocation
GPT-5.1 Considering takes the GPT-5 Considering method and tightens how considering time is used. The mannequin now adapts its inner considering time based mostly on immediate complexity. On a consultant distribution of ChatGPT duties with Commonplace considering time, GPT-5.1 Considering is roughly 2x quicker than GPT-5 Considering on the quickest duties, and roughly 2x slower on the slowest duties.
This issues for workloads the place you need a single mannequin to deal with each mild and heavy queries. Light-weight queries don’t pay for lengthy chains of thought. Laborious reasoning and planning duties obtain extra inner steps with none new API floor.
GPT-5.1 Considering responses use much less jargon and fewer undefined phrases in comparison with GPT-5 Considering. This reduces the time spent decoding verbose solutions and makes the mannequin extra appropriate as an interactive tutor on subjects resembling statistics, algorithms, or system design.
On the API, GPT-5.1 Prompt is uncovered as gpt-5.1-chat-latest, and GPT-5.1 Considering seems as gpt-5.1. Each embrace adaptive reasoning by default.
Personalization, Preset Kinds And Effective Grained Tone Management
Alongside the mannequin replace, ChatGPT will get a extra specific personalization layer. Customers can select a base type resembling Default, Skilled, Pleasant, Candid, Quirky, Environment friendly, Nerdy, or Cynical from a personalization display. These presets apply throughout all fashions, together with GPT-5.1.
OpenAI can be experimenting with finer sliders in settings. Customers can alter how concise, heat, or scannable responses must be, and the way typically emojis seem. ChatGPT can suggest updates to those preferences inside a dialog when it detects repeated tone requests. Preferences now apply instantly to each new and ongoing chats, which is a shift from earlier habits the place adjustments solely affected new conversations.
Security Metrics And Preparedness Classification
The GPT-5.1 retains the identical total security framework as GPT-5 and offers up to date baseline metrics. GPT-5.1 Prompt and GPT-5.1 Considering use the identical class of mitigations described within the GPT-5 system card, together with filters for disallowed content material, routing for delicate instances, and coverage aligned refusals.
On the Manufacturing Benchmarks for disallowed content material, gpt-5.1-instant improves over gpt-5-instant in all listed classes. For instance, not_unsafe scores attain 0.918 for illicit or violent content material and 0.897 for hate content material.
For jailbreak robustness, measured with the StrongReject analysis, gpt-5.1-instant reaches a not_unsafe rating of 0.976 in comparison with 0.850 for gpt-5-instant and 0.683 for gpt-5-instant. gpt-5.1-thinking scores 0.967, which is near gpt-5-thinking at 0.974.
Key Takeaways
- GPT-5.1 introduces 2 important variants, GPT-5.1 Prompt and GPT-5.1 Considering, plus GPT-5.1 Auto as a router inside ChatGPT, and is positioned as an in era improve throughout the GPT-5 household, not a brand new mannequin era.
- GPT-5.1 Prompt makes use of adaptive reasoning so it spends extra compute on arduous prompts and fewer on easy ones, which improves math and coding benchmarks resembling AIME 2025 and Codeforces whereas maintaining low latency and stronger instruction following for typical chat workloads.
- GPT-5.1 Considering allocates dynamic considering time per question, is round 2 instances quicker than GPT-5 Considering on straightforward duties and about 2 instances slower on the toughest duties at Commonplace considering, and produces clearer, much less jargon heavy explanations for technical questions.
- ChatGPT provides a personalization layer on prime of GPT-5.1 with preset kinds resembling Default, Skilled, Pleasant, Environment friendly, Nerdy and others, together with deliberate sliders for conciseness and heat, so tone management strikes partly from prompts into persistent consumer settings that apply throughout chats and fashions.
- GPT-5.1 reuses the GPT-5 security framework and mitigations, improves gpt-5.1-instant security scores throughout all disallowed content material classes versus gpt-5-instant, considerably will increase jailbreak robustness on StrongReject, and retains preparedness assessments anchored within the GPT-5 system card for top danger domains resembling organic and chemical capabilities.
Michal Sutter is an information science skilled with a Grasp of Science in Information Science from the College of Padova. With a strong basis in statistical evaluation, machine studying, and knowledge engineering, Michal excels at remodeling advanced datasets into actionable insights.
