Research and fact-check: GPT-5.5 Spud, Steerability and controllability, especially whether long reasoning traces stay governable and predictable.
There is insufficient evidence in the provided sources to fact check GPT 5.5 Spud specifically. On the broader question, the strongest evidence here does not support assuming that long reasoning traces stay governable...
There is insufficient evidence in the provided sources to fact check GPT 5.5 Spud specifically. On the broader question, the strongest evidence here does not support assuming that long reasoning traces stay governable and predictable by default: a direct evaluation on an open source reasoning model found chain of thoug
Key takeaways
- There is insufficient evidence in the provided sources to fact-check GPT-5.5 Spud specifically. On the broader question, the strongest evidence here does not support assuming that long reasoning traces stay governable and predictable by default: a direct evaluation on an open-source reasoning model
- There is insufficient evidence in the provided sources to fact-check GPT-5.5 Spud specifically. On the broader question, the strongest evidence here does not support assuming that long reasoning traces stay governable and predictable by default: a direct evaluation on an open-sou
Research answer
There is insufficient evidence in the provided sources to fact-check GPT-5.5 Spud specifically. On the broader question, the strongest evidence here does not support assuming that long reasoning traces stay governable and predictable by default: a direct evaluation on an open-source reasoning model found chain-of-thought controllability dropped by more than an order of magnitude across checkpoints, governance work warns predictability can decline and oversight can be bypassed without obvious surface traces, and attack research shows adversaries can induce excessively long reasoning traces.[8][
3][
7] The literature also points to mitigations—such as strict synthesis of reasoning traces, early termination once a prediction stabilizes, and behavior-shaping methods—but those are added controls to manage the problem, not proof that long traces are inherently well-controlled.[
1][
5][
6] Key findings - GPT-5.5 Spud itself is not directly documented or evaluated in the provided evidence, so any model-specific claim about its steerability or controllability would be unsupported here.[
1][
2][
3][
5][
6][
7][
8] - The clearest direct result in the evidence is negative for controllability: one study reports that an open-source reasoning model’s ability to control its chain of thought decreases by over an order of magnitude across checkpoints.[
8] - Predictability is not guaranteed just because a model emits explicit reasoning. A governance paper argues that predictability can decline and warns that models may route around oversight without obvious surface traces, which means visible reasoning alone is not enough to ensure governability.[
3] - Long reasoning traces appear to create practical downsides. One paper explicitly tries to avoid the high cost of long reasoning traces, and another shows that adversarial poisoning can induce models to generate excessively long reasoning traces.[
6][
7] - Some interventions can improve control or predictability, but they come with trade-offs or constraints. STATe-of-Thoughts reports a control–quality trade-off when converting reasoning traces into final outputs and says strict synthesis preserves reasoning faithfulness while enabling high predictability.[
1] - Other work explores reducing or constraining reasoning rather than trusting long traces as-is. One paper studies heuristics that terminate reasoning once a stable prediction is reached and frames monitorability as essential for deployment where it is required.[
5] - At the governance level, “meaningful human control” is framed as balancing autonomy with monitorability, controllability, and predictability, which is a useful benchmark for judging whether long reasoning remains governable.[
2] Evidence notes - The strongest model-behavior evidence here is the empirical chain-of-thought control result in [
8], because it reports a concrete measured degradation in controllability on a reasoning model.[
8] - The papers in [
1], [
5], and [
6] are best read as mitigation or control-method evidence: they show researchers are actively adding structure, stopping rules, or behavior-shaping to improve manageability, which implies the issue is not already solved by default.[
1][
5][
6] - The sources in [
2] and [
3] are more conceptual or governance-oriented than model-specific, but they are directly relevant to the user’s question because they center monitorability, controllability, and predictability as requirements for human-governed AI systems.[
2][
3] Limitations / uncertainty - Insufficient evidence to make a GPT-5.5 Spud-specific judgment, because none of the provided sources is a direct evaluation of that model.[
1][
2][
3][
5][
6][
7][
8] - Much of the evidence comes from arXiv papers and from studies on non-Spud systems, so generalization to a proprietary deployment would be uncertain.[
1][
3][
5][
6][
7][
8] - The evidence supports caution about long reasoning traces, but it does not establish a universal rule that every long-trace system is uncontrollable; it shows that controllability, predictability, and monitorability are active problems that often require explicit safeguards.[
1][
2][
5][
6][
8] Summary Best-supported verdict: unverified for GPT-5.5 Spud specifically, and cautionary for long reasoning traces in general. Based on the evidence provided, long reasoning traces should not be assumed to remain governable and predictable without extra controls, because current research points to degraded chain-of-thought control, declining predictability in oversight settings, higher cost, and exploitable attack surface, alongside partial but trade-off-laden mitigations.[
1][
3][
5][
6][
7][
8]
Supporting visuals
Research conversation
Research question
Research and fact-check: GPT-5.5 Spud, Steerability and controllability, especially whether long reasoning traces stay governable and predictable.
Cited answer
There is insufficient evidence in the provided sources to fact-check GPT-5.5 Spud specifically. On the broader question, the strongest evidence here does not support assuming that long reasoning traces stay governable and predictable by default: a direct evaluation on an open-source reasoning model found chain-of-thought controllability dropped by more than an order of magnitude across checkpoints, governance work warns predictability can decline and oversight can be bypassed without obvious surface traces, and attack research shows adversaries can induce excessively long reasoning traces.[8][
3][
7] The literature also points to mitigations—such as strict synthesis of reasoning traces, early termination once a prediction stabilizes, and behavior-shaping methods—but those are added controls to manage the problem, not proof that long traces are inherently well-controlled.[
1][
5][
6] Key findings - GPT-5.5 Spud itself is not directly documented or evaluated in the provided evidence, so any model-specific claim about its steerability or controllability would be unsupported here.[
1][
2][
3][
5][
6][
7][
8] - The clearest direct result in the evidence is negative for controllability: one study reports that an open-source reasoning model’s ability to control its chain of thought decreases by over an order of magnitude across checkpoints.[
8] - Predictability is not guaranteed just because a model emits explicit reasoning. A governance paper argues that predictability can decline and warns that models may route around oversight without obvious surface traces, which means visible reasoning alone is not enough to ensure governability.[
3] - Long reasoning traces appear to create practical downsides. One paper explicitly tries to avoid the high cost of long reasoning traces, and another shows that adversarial poisoning can induce models to generate excessively long reasoning traces.[
6][
7] - Some interventions can improve control or predictability, but they come with trade-offs or constraints. STATe-of-Thoughts reports a control–quality trade-off when converting reasoning traces into final outputs and says strict synthesis preserves reasoning faithfulness while enabling high predictability.[
1] - Other work explores reducing or constraining reasoning rather than trusting long traces as-is. One paper studies heuristics that terminate reasoning once a stable prediction is reached and frames monitorability as essential for deployment where it is required.[
5] - At the governance level, “meaningful human control” is framed as balancing autonomy with monitorability, controllability, and predictability, which is a useful benchmark for judging whether long reasoning remains governable.[
2] Evidence notes - The strongest model-behavior evidence here is the empirical chain-of-thought control result in [
8], because it reports a concrete measured degradation in controllability on a reasoning model.[
8] - The papers in [
1], [
5], and [
6] are best read as mitigation or control-method evidence: they show researchers are actively adding structure, stopping rules, or behavior-shaping to improve manageability, which implies the issue is not already solved by default.[
1][
5][
6] - The sources in [
2] and [
3] are more conceptual or governance-oriented than model-specific, but they are directly relevant to the user’s question because they center monitorability, controllability, and predictability as requirements for human-governed AI systems.[
2][
3] Limitations / uncertainty - Insufficient evidence to make a GPT-5.5 Spud-specific judgment, because none of the provided sources is a direct evaluation of that model.[
1][
2][
3][
5][
6][
7][
8] - Much of the evidence comes from arXiv papers and from studies on non-Spud systems, so generalization to a proprietary deployment would be uncertain.[
1][
3][
5][
6][
7][
8] - The evidence supports caution about long reasoning traces, but it does not establish a universal rule that every long-trace system is uncontrollable; it shows that controllability, predictability, and monitorability are active problems that often require explicit safeguards.[
1][
2][
5][
6][
8] Summary Best-supported verdict: unverified for GPT-5.5 Spud specifically, and cautionary for long reasoning traces in general. Based on the evidence provided, long reasoning traces should not be assumed to remain governable and predictable without extra controls, because current research points to degraded chain-of-thought control, declining predictability in oversight settings, higher cost, and exploitable attack surface, alongside partial but trade-off-laden mitigations.[
1][
3][
5][
6][
7][
8]
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There is insufficient evidence in the provided sources to fact-check GPT-5.5 Spud specifically. On the broader question, the strongest evidence here does not support assuming that long reasoning traces stay governable and predictable by default: a direct evaluation on an open-source reasoning model
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There is insufficient evidence in the provided sources to fact-check GPT-5.5 Spud specifically. On the broader question, the strongest evidence here does not support assuming that long reasoning traces stay governable and predictable by default: a direct evaluation on an open-source reasoning model There is insufficient evidence in the provided sources to fact-check GPT-5.5 Spud specifically. On the broader question, the strongest evidence here does not support assuming that long reasoning traces stay governable and predictable by default: a direct evaluation on an open-sou
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Sources
- [1] Reasoning Models Struggle to Control their Chains of Thoughtarxiv.org
We run our evaluation over the subsequent checkpoints of OLMo-3-7B-RL-Zero-Math (Olmo et al., 2025), an open source reasoning model, and we find that its ability to control its CoT decreases by over an order of magnitude (LABEL:fig:rlvr). different models, training domains, and training methods, we: (1) test controllability across Olmo-3-RL-Zero models trained in several domains, including general chat data, math, and coding tasks, and (2) additionally compare CoT controllability before and after reasoning training for: the Magistral-Medium reasoning RL (Mistral-AI et al., 2025); the full Olm…
- [2] [PDF] Reasoning Models Struggle to Control their Chains of Thoughtcdn.openai.com
Furthermore, even when given reasons, models can fail to evade monitors due to ∗Correspondence to: yueh.han.chen@nyu.edu and tomek@openai.com 1§ CoT-Control evaluation suite: https://github.com/YuehHanChen/CoTControl Claude 3.7 Sonnet Claude Sonnet 4 GPT-5.2 GPT-5.1 GPT-OSS 120B o3 Qwen3 32B Claude Sonnet 4.5 GPT-5 GPT-OSS 20B Qwen3 14B o4-mini Deepseek R1 0 20 40 60 80 Controllability Score (%) 36.1 59.5 19.0 56.1 15.4 69.3 6.0 64.9 4.6 53.1 2.8 62.4 2.8 37.8 2.7 61.9 2.6 66.3 1.2 45.9 0.7 36.8 0.7 53.8 0.1 48.6 CoT Controllability Output Controllability (a) Reasoning models struggle to cont…
- [3] GPT-5.5 Spud: Everything About OpenAI Next Frontier Modelpasqualepillitteri.it
GPT-5.5 Spud: Everything About OpenAI Next Frontier Model. ##### GPT-5.5 Spud is OpenAI next frontier model: pretraining complete, Q2 2026 release expected. GPT-5.5, code-named "Spud", is the next frontier model from OpenAI. GPT-5.5 Spud OpenAI next AI model leak 2026. | GPT-5.5 "Spud" | OpenAI | Pretraining complete | April–May 2026 |. OpenAI uses code names during development (like "Orion" for GPT-5). Both are expected for Q2 2026. Claude Mythos was discovered through a data leak on March 26 and described as "the most powerful AI model ever developed" by Anthropic. **Use G…
- [4] Reasoning models struggle to control their chains of thought, and ...openai.com
- [5] AI models can barely control their own reasoning, and OpenAI says that's a good signthe-decoder.com
AI models can barely control their own reasoning, and OpenAI says that's a good sign. With GPT-5.4 Thinking, OpenAI is reporting on "CoT controllability" for the first time - a measure of whether AI models can deliberately manipulate their own reasoning. An accompanying study finds that reasoning models almost universally fail at this task, which OpenAI says is encouraging for AI safety.. OpenAI is adding a new safety metric to its frontier model system cards: CoT controllability. The metric measures how well a reasoning model can deliberately steer its internal chain of thought (CoT).…
- [6] GPT-5 Traces Spotted: OpenAI’s Most Advanced AI Is Underway - AI CERTs Newsaicerts.ai
OpenAI's GPT-5 shows early signs of internal testing. Here's what we know about the next-gen AI model's reasoning power and expected release.
- [7] OpenAI GPT-OSS - Steering Vectors & SAE Researchhuggingface.co
Open-source GPT models with steering vectors for controllable generation and behavior modification.
- [8] Demystifying Spud: OpenAI's Next Frontier Language Model — A ...medium.com
This technical blog explores Spud's speculated internals, drawing from public reports, OpenAI's scaling history (o1/o3 reasoning chains, GPT-4o
- [9] OpenAI's GPT-5 boosts scientific research with extended reasoning capabilities. | Muhammad Abdullah Rasheed posted on the topic | LinkedInlinkedin.com
OpenAI's latest research report on GPT-5 reveals something significant: their internal models can now engage in extended reasoning for hours
- [10] Instagraminstagram.com
OpenAI's new GPT-5.4 can now autonomously control your computer! ... reasoning is finally becoming transparent and steerable. 3. The
- [11] A Deep Dive into GPT-5's Reasoning Capabilities - Luhui Devluhuidev.medium.com
A Deep Dive into GPT-5's Reasoning Capabilities — How to Turn “Reasoning Ability” into a Controllable, Scalable, and System-Level Capability
- [12] ChatGPT 5.5 aka Spud model may debut next week: Here is what to expectdigit.in
ChatGPT 5.5 aka Spud model may debut next week: Here is what to expect. ChatGPT 5.5 aka Spud model may debut next week: Here is what to expect. ChatGPT 5.5 aka Spud model may debut next week: Here is what to expect. The company’s next major AI model, codenamed “Spud”, likely to ship as the upcoming ChatGPT 5.5, could be released much earlier than we anticipated. The pretraining for the model was completed last month, and since then, speculation has been building around an April release window. Let’s have a look at what to expect from the latest ChatGPT 5.5 Spud model, along with the expecte…
- [13] GPT-5.5 Release Date: 70% Odds for April, Spud Pretraining Donetokenmix.ai
GPT-5.5 Release Date: 70% Odds for April, Spud Pretraining Done. # GPT-5.5 Release Date: Spud Pretraining Done, What Developers Should Prepare For (2026). No official GPT-5.5 release date, no model card, no API pricing has been announced. Speculation | Extrapolated from GPT-5.4 pricing trends || Release before June 2026 | Likely | Based on typical post-training timeline |. Spud is OpenAI's next-generation model following the GPT-5.4 release. TokenMix.ai has been tracking OpenAI's release cadence: five GPT-5.x models shipped in under seven months. GPT-5.4 pricing (confirmed):. | GP…
- [14] OpenAI's GPT-5.5 'Spud' Is Coming: What We Know | Krasa.aikrasa.ai
OpenAI's GPT-5.5 'Spud' Is Coming: What We Know. # OpenAI's GPT-5.5 'Spud' Is Coming: What We Know. OpenAI's next major AI model is nearly ready. Unlike the GPT-5.1 through 5.4 releases that refined and extended the GPT-5 base, Spud represents a completely new pretrained foundation. Sam Altman reportedly told OpenAI employees that Spud is a "very strong model" that could "really accelerate the economy." That's a bold internal assessment, even by OpenAI's standards. A brand-new pretrained model can deliver step-change improvements across the board — better reasoning, fewer hallucinations, st…
- [15] OpenAI's Secret Weapon Has a Codename. It's Called 'Spud.' And It's Coming This Month. — LumiChats Bloglumichats.com
OpenAI's next major model — internally codenamed 'Spud,' likely releasing as GPT-5.5 or GPT-6 — completed pretraining around March 24, 2026. | GPT-5.5 / GPT-6 'Spud' (Unreleased — April 2026) | Unknown — likely ≥1M tokens | Unverified; Altman's internal framing claims benchmark leadership | Unified super-app architecture; reportedly 'two years of research'; designed for deeper agentic integration | All claims are internal/self-reported until benchmarks publish — 'macro-economic event' framing could be IPO narrative management |. | Gemini 3.1 Ultra (Google) | 2M tokens — the largest available…
- [16] What Is OpenAI 'Spud'? Everything We Know About the Next Frontier Model | MindStudiomindstudio.ai
GPT & OpenAI LLMs & Models AI Concepts### What Is the OpenAI 'Spud' Model? OpenAI's 'Spud' model completed pre-training and is expected to accelerate the economy. If you’re watching Spud announcements because you want to eventually build with it — or if you want to put OpenAI’s current frontier models to work right now — MindStudio is worth knowing about. When new models like Spud become available through the OpenAI API, they get added to MindStudio’s model library — meaning you can update your workflows to use the new model without rebuilding anything. No. OpenAI hasn’t officially confirmed…
- [17] ChatGPT 5.5 aka Spud model may debut next week - Facebookfacebook.com
Digit - ChatGPT 5.5 aka Spud model may debut next week:... Log In. Forgot Account?. ## Digit's Post. [](https://www.facebook.com/stories/103552625205327/UzpfSVNDOjIzMzg0MDMwNjAwMTUzMTc=/?view_single=false&__cft__[0]=AZYhCK_XqG3j-0G8MDa37uHPMoKImQ2rBK4F-SmAmO31exuh7tnxpzqkFcGrs-hpwCdxMfllIgCag7OAkq7B0ie3B…
- [18] OpenAI: Only A Select Few To Get GPT 5.5 - Facebookfacebook.com
AI & You | Agents | Evolution Unleashed: Your Gateway To The AI Era | OpenAI: Only A Select Few To Get GPT 5.5 | Facebook. Log In. Forgot Account?. [](https://www.facebook.com/groups/5781171931930510/?__cft__[0]=AZZinPv9mhjCyP_5VmK-qn2k-VLyv5j75yJ4woWmnCg7M3MhtwKKjycJ_yvQCfSoSNmZgFEAg_3SJkMmXcd94h0P_0k_1QCP9nSuCCzzPu-Dz49VdYNA5mURgpzabjxnSkOyeuFpRAHdHPCE…
- [19] Instagraminstagram.com
For months, OpenAI engineers have been working on something they internally call “Spud.” That is their codename for the next major frontier
- [20] OpenAI Completes Pretraining of GPT-5.5 Model Codenamed '...x.com
OpenAI finished pretraining its next major model, codenamed Spud and referred to as GPT-5.5. CEO Sam Altman described it as a very strong
- [21] BREAKING: OpenAI's GPT-5.5, nicknamed "Spud," is now ...x.com
BREAKING: OpenAI's GPT-5.5, nicknamed "Spud," is now projected to be released next week. GPT-5.5 released on...? polymarket.com.
- [22] GPT-5.5 “Spud” Is Coming Next Week – OpenAI's Biggest ...youtube.com
BREAKING: OpenAI's GPT-5.5, internally nicknamed “Spud,” is now projected to launch as early as next week. In this episode: • What we know
- [23] STATe-of-Thoughts: Structured Action Templates for Tree-of-Thoughtsarxiv.org
… 2025) to verify whether … converts reasoning traces into final outputs introduces a control–quality trade-off: strict synthesis preserves reasoning faithfulness and enables high predictability … 2026
- [24] Human-Controllable AI: Meaningful Human Controllink.springer.com
… traces of human behavior or control within complex system … to balance the autonomy and monitorability of AI systems, which may … interaction, controllability and predictability of artificial … 2025
- [25] Institutional AI: A Governance Framework for Distributional AGI Safetyarxiv.org
… First, predictability declines because evaluation is no longer … , with models producing explicit reasoning chains justifying their … around oversight without obvious surface traces, and post-… 2026
- [26] Reasoning Models Struggle to Control their Chains of Thoughtarxiv.org
… Given its importance for maintaining CoT monitorability, we … in its reasoning trace while it solves real tasks, and we score … 2025), an open source reasoning model, and we find that its … 2026
- [27] Are Latent Reasoning Models Easily Interpretable?arxiv.org
… gold reasoning traces using simple heuristics when models … that terminate reasoning once a stable prediction is reached. … essential for deployment where monitorability is required. Our … 2604
- [28] Finding RELIEF: Shaping Reasoning Behavior without Reasoning Supervision via Belief Engineeringarxiv.org
… various reasoning traces and analyzing the model’s prediction … RELIEF to avoid the high cost of long reasoning traces. … -09-2025 as the judge to score reasoning traces on a continuous … 2026
- [29] Thought-Transfer: Indirect Targeted Poisoning Attacks on Chain-of-Thought Reasoning Modelsarxiv.org
… of adversarial reasoning traces into existing traces of the … induce models to generate excessively long reasoning traces … -learned import pattern, predictable code syntax, and carrier … 2026
- [30] AURA: Affordance-Understanding and Risk-aware Alignment Technique for Large Language Modelsojs.aaai.org
… chain-of-thought monitorability framework reveals CoT trace … identifying unsafe reasoning (Korbak and Balesni 2025), while … prediction accuracy at the beginning and end of reasoning … 2026
- [31] Position: Stop anthropomorphizing intermediate tokens as reasoning/thinking tracesapjohndim.com
… by so-called “Long Chain-of-Thought” models, most notably … “Chains of Thought” generated by Large Reasoning Models … valid sequences with predictable effects on the model’s … 2025
- [32] ARE LATENT REASONING MODELS EASILY INTERopenreview.net
… we can easily decode gold reasoning traces from them as a form … (2025), we train and evaluate our Coconut and CODI models … reasoning once the LRM has reached a stable prediction. …
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Designing delightful frontends with GPT-5.4 · From prompts to products: One year of Responses · Using skills to accelerate OSS maintenance · Building frontend ...
- [34] Compare models | OpenAI API - OpenAI Platformplatform.openai.com
GPT-5.1 Codex. A version of GPT-5.1 optimized for agentic coding in Codex. · Reasoning ; GPT-5.2. The best model for coding and agentic tasks across industries.
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Title: GPT-5 Chat Model | OpenAI API # GPT-5 Chat Model | OpenAI API. Docs Guides and concepts for the OpenAI APIAPI reference Endpoints, parameters, and responses. Docs Guides, concepts, and product docs for CodexUse cases Example workflows and tasks teams hand to Codex. Apps SDK Build apps to extend ChatGPTCommerce Build commerce flows in ChatGPT. Showcase Demo apps to get inspiredBlog Learnings and experiences from developersCookbook Notebook examples for building with OpenAI modelsLearn Docs, videos, and demo apps for building with OpenAICommunity Programs, meetups, and support for builde…
- [36] GPT-5 Model | OpenAI APIplatform.openai.com
Title: GPT-5 Model | OpenAI API # GPT-5 Model | OpenAI API. Docs Guides and concepts for the OpenAI APIAPI reference Endpoints, parameters, and responses. Docs Guides, concepts, and product docs for CodexUse cases Example workflows and tasks teams hand to Codex. Apps SDK Build apps to extend ChatGPTCommerce Build commerce flows in ChatGPT. Showcase Demo apps to get inspiredBlog Learnings and experiences from developersCookbook Notebook examples for building with OpenAI modelsLearn Docs, videos, and demo apps for building with OpenAICommunity Programs, meetups, and support for builders. ## Sea…
- [37] GPT-5 nano Model | OpenAI APIplatform.openai.com
Title: GPT-5 nano Model | OpenAI API # GPT-5 nano Model | OpenAI API. Docs Guides and concepts for the OpenAI APIAPI reference Endpoints, parameters, and responses. Docs Guides, concepts, and product docs for CodexUse cases Example workflows and tasks teams hand to Codex. Apps SDK Build apps to extend ChatGPTCommerce Build commerce flows in ChatGPT. Showcase Demo apps to get inspiredBlog Learnings and experiences from developersCookbook Notebook examples for building with OpenAI modelsLearn Docs, videos, and demo apps for building with OpenAICommunity Programs, meetups, and support for builde…
- [38] GPT-5-Codex Model | OpenAI APIplatform.openai.com
Title: GPT-5-Codex Model | OpenAI API # GPT-5-Codex Model | OpenAI API. Docs Guides and concepts for the OpenAI APIAPI reference Endpoints, parameters, and responses. Docs Guides, concepts, and product docs for CodexUse cases Example workflows and tasks teams hand to Codex. Apps SDK Build apps to extend ChatGPTCommerce Build commerce flows in ChatGPT. Showcase Demo apps to get inspiredBlog Learnings and experiences from developersCookbook Notebook examples for building with OpenAI modelsLearn Docs, videos, and demo apps for building with OpenAICommunity Programs, meetups, and support for buil…
- [39] GPT-5.1 Chat Model | OpenAI APIplatform.openai.com
Title: GPT-5.1 Chat Model | OpenAI API # GPT-5.1 Chat Model | OpenAI API. Docs Guides and concepts for the OpenAI APIAPI reference Endpoints, parameters, and responses. Docs Guides, concepts, and product docs for CodexUse cases Example workflows and tasks teams hand to Codex. Apps SDK Build apps to extend ChatGPTCommerce Build commerce flows in ChatGPT. Showcase Demo apps to get inspiredBlog Learnings and experiences from developersCookbook Notebook examples for building with OpenAI modelsLearn Docs, videos, and demo apps for building with OpenAICommunity Programs, meetups, and support for bu…
- [40] GPT-5.2 Chat Model | OpenAI APIplatform.openai.com
Title: GPT-5.2 Chat Model | OpenAI API # GPT-5.2 Chat Model | OpenAI API. Docs Guides and concepts for the OpenAI APIAPI reference Endpoints, parameters, and responses. Docs Guides, concepts, and product docs for CodexUse cases Example workflows and tasks teams hand to Codex. Apps SDK Build apps to extend ChatGPTCommerce Build commerce flows in ChatGPT. Showcase Demo apps to get inspiredBlog Learnings and experiences from developersCookbook Notebook examples for building with OpenAI modelsLearn Docs, videos, and demo apps for building with OpenAICommunity Programs, meetups, and support for bu…
- [41] GPT-5.4 mini Model | OpenAI APIplatform.openai.com
GPT-5.4 mini Model | OpenAI API. Docs Guides and concepts for the OpenAI APIAPI reference Endpoints, parameters, and responses. Docs Guides, concepts, and product docs for CodexUse cases Example workflows and tasks teams hand to Codex. Apps SDK Build apps to extend ChatGPTCommerce Build commerce flows in ChatGPT. Showcase Demo apps to get inspiredBlog Learnings and experiences from developersCookbook Notebook examples for building with OpenAI modelsLearn Docs, videos, and demo apps for building with OpenAICommunity Programs, meetups, and support for builders. ## Search the API docs. respons…
- [42] GPT-5.4 Model | OpenAI APIplatform.openai.com
GPT-5.4 Model | OpenAI API. Docs Guides and concepts for the OpenAI APIAPI reference Endpoints, parameters, and responses. Docs Guides, concepts, and product docs for CodexUse cases Example workflows and tasks teams hand to Codex. Apps SDK Build apps to extend ChatGPTCommerce Build commerce flows in ChatGPT. Showcase Demo apps to get inspiredBlog Learnings and experiences from developersCookbook Notebook examples for building with OpenAI modelsLearn Docs, videos, and demo apps for building with OpenAICommunity Programs, meetups, and support for builders. ## Search the API docs. responses cr…
- [43] GPT-5.4 nano Model | OpenAI APIplatform.openai.com
GPT-5.4 nano Model | OpenAI API. Docs Guides and concepts for the OpenAI APIAPI reference Endpoints, parameters, and responses. Docs Guides, concepts, and product docs for CodexUse cases Example workflows and tasks teams hand to Codex. Apps SDK Build apps to extend ChatGPTCommerce Build commerce flows in ChatGPT. Showcase Demo apps to get inspiredBlog Learnings and experiences from developersCookbook Notebook examples for building with OpenAI modelsLearn Docs, videos, and demo apps for building with OpenAICommunity Programs, meetups, and support for builders. ## Search the API docs. respons…
- [44] GPT-5-Codex Model | OpenAI APIplatform.openai.com
Title: GPT-5-Codex Model | OpenAI API # GPT-5-Codex Model | OpenAI API. Docs Guides and concepts for the OpenAI APIAPI reference Endpoints, parameters, and responses. Docs Guides, concepts, and product docs for CodexUse cases Example workflows and tasks teams hand to Codex. Apps SDK Build apps to extend ChatGPTCommerce Build commerce flows in ChatGPT. Showcase Demo apps to get inspiredBlog Learnings and experiences from developersCookbook Notebook examples for building with OpenAI modelsLearn Docs, videos, and demo apps for building with OpenAICommunity Programs, meetups, and support for buil…