OpenAI has released GPT-5.6 for general availability, a three-model family designed to make frontier-level AI practical for more end-to-end knowledge work. Sol is the flagship model for demanding tasks; Terra is intended to balance performance and cost for everyday work; and Luna is the family’s lowest-cost option. Businesses now need to decide what work they can trust AI to complete that it could not reliably or affordably handle before.

OpenAI says GPT-5.6 lets businesses use stronger AI for research, document work, software development, analysis, computer use, and other multi-step tasks without facing the same cost and speed tradeoffs as before. In its benchmark comparisons, OpenAI says Sol outperforms earlier and competing frontier models with fewer tokens, lower estimated cost, and, in some tests, less time to complete the work. The model family is built for longer assignments that draw on tools and connected information, letting teams choose a model and effort setting that fits the complexity and cost of the work.

Teams using AI for research, documents, presentations, spreadsheets, coding, and other work involving company information will need to decide when the added capability justifies the cost, oversight, access controls, and safeguards.

In short, GPT-5.6 may make frontier AI useful for more end-to-end knowledge work, but businesses still need to determine which work they can safely trust it to complete.

Frontier intelligence refers here to AI capability across demanding work such as coding, research, computer use, science, health, and cybersecurity.

This three-model AI family is designed to let businesses use frontier-level capability for longer, multi-step knowledge work while choosing the cost and effort appropriate to each task.

OpenAI has released GPT-5.6 for general availability after a limited preview, introducing a three-model family meant to give businesses different levels of capability and cost. Sol is the flagship model, Terra is intended to balance performance and cost for everyday tasks, and Luna offers the lowest-cost option in the family.

GPT-5.6 Sol sets a new standard for both intelligence and efficiency, OpenAI says, and achieves state-of-the-art results across coding, knowledge work, cybersecurity, and science. The company says Sol outperforms earlier and competing frontier models with fewer tokens and at a lower estimated cost. OpenAI says businesses can complete more successful work for the same spend or achieve similar results for less total cost.

OpenAI also says Sol has stronger computer-use and design judgment, allowing it to inspect a rendered result, refine it, and return work that is ready to use.

Ultra is a separate highest-capability setting for the most demanding work. It coordinates multiple agents across parallel workstreams to finish complex tasks faster, using more tokens in exchange for stronger results and faster completion.

The model family gives businesses different ways to match model cost and capability to the work at hand, with ultra available when a task calls for more time and computing power. OpenAI’s claims about results, cost, and speed are tested in the benchmark comparisons that follow.

Businesses weighing performance against cost will need to evaluate whether OpenAI’s benchmark results support the idea that they can run this level of capability more often.

For a business deciding whether to use a stronger model for research, document work, software development, or analysis, OpenAI’s argument comes down to this: GPT-5.6 can take on more demanding work while keeping the cost and waiting time manageable enough for repeated use.

OpenAI included several benchmark results in the launch. The five below speak most directly to knowledge work, while the coding, science, health, and cybersecurity results show how far the company says the model’s gains extend.

OpenAI also reports detailed gains in other fields:

The benchmark results span web research, computer use, coding, science, health, and cybersecurity, and show the range of work OpenAI believes GPT-5.6 can handle with greater efficiency. But, if advanced AI becomes more economical, how does it actually take on work that unfolds across many steps?

Programmatic Tool Calling is an API feature that lets GPT-5.6 write and run small JavaScript programs to coordinate the tools available in a Responses API request. Those programs can call tools in parallel, process intermediate results, monitor progress, and choose the next action as work unfolds.

For tool-heavy tasks, the program can filter large amounts of intermediate data, keep the information that matters, and adapt the workflow as it goes. With Programmatic Tool Calling, developers do not have to script every step in advance or send every tool response back through the model before it can continue. OpenAI says that approach can reduce tokens, model round trips, and the guidance required to complete the task.

When a task warrants more time and computing power, GPT-5.6 can move beyond its default effort setting. Max gives the model more time than xhigh to explore alternatives, run checks, and revise its approach. Ultra is built for the most demanding work, coordinating four agents in parallel by default and using more tokens in exchange for stronger results and faster completion.

Developers can build similar workflows through the Responses API’s multi-agent beta, which lets GPT-5.6 run concurrent subagents and combine their work in a single request.

Clio, a legal-technology company, said it saw those gains in legal research and document workflows:

“Across legal research and document workflows, GPT-5.6 is already delivering the kind of efficiency gains that change product economics. In our combined evaluation suite, it uses 14% fewer tokens while improving quality across legal research and transactional law use cases. For multi-step document analysis, Programmatic Tool Calling cuts prompt tokens by 38% with no quality loss.” —Angel Faus, VP of Engineering at Clio

GPT-5.6’s ability to work through multi-step tasks using tools and connected information becomes most useful when a company needs research, documents, presentations, spreadsheets, and other work teams can use and share.

GPT-5.6 is meant to work from the information a business already uses every day. In ChatGPT Work, users can connect approved apps and tools such as Slack, Microsoft Teams, Google Drive, SharePoint, email, calendars, project trackers, and other internal systems. GPT-5.6 can pull relevant context from those sources and use it to create documents, decks, spreadsheets, analyses, and other shareable work.

The user remains in control of what ChatGPT Work can access and when it needs approval before taking action. That matters when a task involves company files, internal messages, customer information, or work that will be shared with colleagues or clients. It also gives teams a way to move from a request to finished material without manually collecting and uploading every source first.

OpenAI says GPT-5.6 improves the quality of presentations, documents, and spreadsheets. It can create editable presentations from a prompt and source material, using layouts, hierarchy, and design that fit the content. The company also says the model follows complex reference formats more faithfully, handles equations and financial models with greater precision, and produces documents and spreadsheets with stronger typography, spacing, and page or worksheet layout.

The difference is especially visible when a task starts with an existing template or reference deck. OpenAI says GPT-5.6 can infer a deck’s design system, including its layouts, typography, spacing, colors, recurring content patterns, and rules embedded in the Slide Master. Its stronger computer-use capabilities also let it inspect and refine the rendered result, helping it catch visual and functional issues before handing work back.

“Across 20 challenging client workflows and hundreds of decks in Model ML’s FinBench, it used 39% fewer tokens per deck than Fable while producing more polished, legible decks with clearer, more accurate data visualizations that required less rework before sharing.” —Chaz Englander, Co-Founder & CEO at Model ML

As GPT-5.6 works with more consequential company information and produces work that people may act on, businesses also need to understand the limits, safeguards, and access controls around those capabilities.

OpenAI calls GPT-5.6 its strongest cybersecurity model and says it delivers frontier cyber performance with significantly fewer tokens. On ExploitBench 2, which measures progress from finding vulnerable code to executing an exploit, OpenAI says Sol scored 73.5%, compared with GPT-5.5’s 47.9% at a comparable output-token budget.

OpenAI says GPT-5.6 is more capable than earlier models in cybersecurity and biology, though it does not cross the company’s Critical threshold in either area. In biology, OpenAI says the model can support legitimate research without providing the end-to-end capability needed to create, engineer, or synthesize a highly dangerous new threat.

Those capabilities can also support defensive work such as secure code review, patching, threat modeling, and blue teaming, where security teams test and strengthen an organization’s defenses. OpenAI Daybreak’s Trusted Access for Cyber gives qualified individuals and organizations access to more of that defensive capability in authorized environments, including vulnerability triage, malware analysis, detection engineering, and patch validation.

Before general availability, OpenAI says it ran its most intensive safety evaluation period to date, combining human red teaming, external-expert testing, and black-box automated red teaming that used approximately 700,000 A100e GPU hours. The scale of that testing shows the effort OpenAI put into finding weaknesses before release; it does not, however, guarantee that the system is free of future failures or misuse.

OpenAI says GPT-5.6 uses layered safeguards for greater accuracy and redundancy, with the ability to adapt as new attacks emerge. Protections trained into the model work alongside real-time checks, continuous monitoring, and account-level enforcement. That gives the system more than one opportunity to catch harmful activity if another layer does not work as intended.

The company also uses a reasoning monitor that reviews a conversation for potential harm. OpenAI says this can preserve legitimate defensive work while blocking serious misuse, with the most sensitive capabilities reserved for verified users through Trusted Access. Some protections use test-time reasoning, allowing OpenAI to update them when it finds gaps without retraining classifiers from scratch.

OpenAI says Sol’s cyber safeguards block roughly ten times more potentially harmful activity than previous models. The company acknowledges that stricter controls can interrupt benign use, so ChatGPT and Codex allow users to retry prompts on lower-capability models. OpenAI says these safeguards will start conservatively and the company will work to reduce that friction as it learns from real-world use.

Businesses considering GPT-5.6 will need to weigh those controls alongside the model’s capability, access level, and cost.

GPT-5.6 is available across several OpenAI products, but what it can access and do depends on where a user is working.

API pricing is set per 1 million tokens. Sol costs $5 for input and $30 for output; Terra costs $2.50 for input and $15 for output; Luna costs $1 for input and $6 for output.

Prompt caching can make repeated API work faster and cheaper. When requests begin with the same instructions, examples, or other common material, OpenAI can reuse that prompt prefix rather than processing it from scratch each time. GPT-5.6 supports explicit cache breakpoints and a minimum cache life of 30 minutes. Cache writes cost 1.25 times the standard input rate, while cached reads receive a 90% discount.

Businesses need to determine which work they can trust GPT-5.6 to complete, which model and effort setting can complete it most cost-effectively, and which consequential tasks still require human review or approval.

Q: What is GPT-5.6?
A: GPT-5.6 is OpenAI’s three-model family for general availability. Sol is the flagship model for demanding work, Terra balances performance and cost for everyday tasks, and Luna is the family’s lowest-cost option. Users can choose a model and effort setting based on the work they need to complete.

Q: What can GPT-5.6 do?
A: OpenAI says GPT-5.6 can support research, document work, software development, analysis, web browsing, computer use, science, health, and cybersecurity. In ChatGPT Work, it can create documents, presentations, spreadsheets, analyses, and other shareable work.

Q: How does GPT-5.6 handle longer, multi-step tasks?
A: Programmatic Tool Calling lets GPT-5.6 write and run small JavaScript programs that coordinate the tools available in a Responses API request. The programs can call tools in parallel, process intermediate results, monitor progress, and choose the next action as work unfolds. Developers can also use the Responses API’s multi-agent beta to run concurrent subagents and combine their work in one request.

Q: Can GPT-5.6 work with company apps and files?
A: In ChatGPT Work, users can connect approved apps and files where their work already lives, including Slack, Microsoft Teams, Google Drive, SharePoint, email, calendars, and project trackers. GPT-5.6 can pull relevant information from those sources while users control what it can access and when it needs approval before taking action.

Q: What is Ultra?
A: Ultra is the highest-capability setting for the most demanding work. It coordinates four agents in parallel by default and uses more tokens in exchange for stronger results and faster completion. OpenAI says it is suited to tasks where those gains justify the additional AI spend.

Q: Why would a business use Terra or Luna instead of Sol?
A: A team may use a lower-cost model for routine work and reserve Sol for jobs that need more capability. OpenAI says Terra surpasses GPT-5.5 at a lower cost, while Luna nearly matches GPT-5.5’s peak performance at less than half the estimated cost.

Q: What should businesses test before using GPT-5.6?
A: Businesses need to determine which work they can trust GPT-5.6 to complete, which model and effort setting can do it most cost-effectively, and which tasks still require human review or approval. They also need to weigh capability, access level, cost, and safeguards.

GPT-5.6 lets businesses use frontier-level AI for more end-to-end knowledge work by offering different levels of capability, cost, and effort. Sol handles the most demanding tasks, Terra is designed to balance performance and cost for everyday work, and Luna is the lowest-cost option.

On Agents’ Last Exam, which measures long-running professional workflows across 55 fields, OpenAI says Sol scored 53.6, 13.1 points above Claude Fable 5 with adaptive reasoning. At medium reasoning, OpenAI says Sol still beat Fable 5 by 11.4 points at roughly one-quarter of the estimated cost, a result that could make Sol practical for more repeated business use.

GPT-5.6 is most relevant to business leaders deciding where AI can take on more work, knowledge-work teams creating research, documents, presentations, spreadsheets, and analyses, developers building with the API, and security teams using AI for defensive work. It also affects organizations that want AI to work with approved company files, internal messages, and customer information.

If OpenAI’s benchmark results hold in day-to-day use, businesses may be able to apply stronger AI more often to work that requires several sources, steps, tools, or revisions. Lower cost and shorter waiting times could expand the range of complex tasks that teams can ask AI to handle.

Businesses need to test which tasks GPT-5.6 can complete reliably enough to trust, which model and effort setting deliver the needed result at an acceptable cost, and where access controls, approvals, and human review remain necessary.

In short, GPT-5.6 may make frontier-level AI practical for more end-to-end business work. Businesses still need to decide where it is reliable, cost-effective, and safe to use.

GPT-5.6 will be useful to businesses when it can complete end-to-end tasks reliably, quickly, and at a cost they can justify, with safeguards and human oversight that fit the work.

Editor’s Note: This article was created by Alicia Shapiro, CMO of AiNews.com, with writing support, AEO/GEO/SEO optimization, image concept development, and editorial structuring support from ChatGPT, an AI assistant. All final editorial decisions, perspectives, and publishing choices were made by Alicia Shapiro.