Today, we are expanding our GPT-6 series by welcoming GPT-6 Sol and GPT-6 Luna to our generally available lineup in Microsoft Foundry . Building on the exceptional customer momentum of GPT-5. 6 Sol and GPT-6 Astra , this launch continues our work to deliver transformative capabilities in Microsoft Foundry that produce less noise and are more capable at completing full tasks with agents .
Explore GPT models in Foundry today Astra brings advanced reasoning , software engineering and computer use to demanding work that requires both judgment and action. Azure customers report a step-change in capabilities, and strong cost-to-performance with the model using fewer, higher-value tokens to drive agents. Completing the lineup, GPT-6 Sol is excellent for general-purpose use, while Luna brings efficient intelligence to high-volume data and preparatory work.
Put the right intelligence behind every agent The right model for a job should be determined through evaluations: an agent handling a complex business decision and one routing routine requests have different needs. Microsoft recommends customers start with GPT-6 Astra for demanding work. For higher-volume workloads, GPT-6 Sol and Luna carry that progress forward, giving you a complementary choice built for production and scale.
GPT-6 Sol for production AI agents and complex workflows GPT-6 Sol , and its proven predecessor—GPT-5. 6 Sol—offer slightly more cost-effective intelligence with frontier efficiency. They support enterprise agents, coding and complex knowledge work, including reasoning across multiple steps, long-context analysis, and workflows that use tools.
For teams evaluating their next production workload or migrating off a legacy model, Sol is a strong starting point. GPT-6 Luna for efficient, high-volume AI workloads GPT-6 Luna is Sol’s smaller, faster sibling, built for high-volume work. Use it for extraction, summarization, request routing, and routine customer interactions.
Reserve deeper reasoning for the steps that need it, rather than applying the same model to every task. As the GPT-6 lineup expands, the opportunity is not simply to choose a newer model, but to improve what your agents can accomplish while saving money. Customers should look beyond pricing per token and seek to understand cost per task , which is a better measure for understanding the ROI of AI .
The accompanying chart illustrates why enterprise customers on Microsoft Foundry are switching to GPT-5. 6 Sol and the latest GPT-6 offerings. Foundry brings evaluation and monitoring together so teams can make those decisions with evidence.
The real measure of that progress is what customers can do in production, which is why Foundry has always encouraged model choice and an open, interoperable stack. The Foundry advantage, in customers’ words Access to frontier models is only the starting point. Foundry pairs GPT-6 intelligence with the breadth of deployment options enterprise production demands.
Today, Standard deployment is available for Astra, Sol and Luna across all 28 Global regions, and US and EU Data Zones; Provisioned Throughput for Astra and Sol across Global regions and US and EU Data Zones; and Priority Processing for Sol across Global regions and US Data Zones . The breadth and performance of Azure is why OpenAI continues to launch first on Azure, and why sophisticated customers like Manus choose Foundry.
Azure OpenAI models provide a core layer of intelligence powering Manus. Through Azure, we reliably integrate advanced models into our agentic workflows, enabling Manus to understand user intent, plan tasks, and execute complex work. Responsive Microsoft technical support and rapid access to new model capabilities help us iterate quickly and deliver a leading, reliable AI experience for our users.
—Tao Zhang, Co-Founder & Product Partner, Manus For customers getting started with AI on Azure : choose Global for flexible, pay-per-token capacity, or supported Data Zone deployments for processing-location requirements. Priority Processing is a priority lane for responsive, pay-as-you-go experiences, with Provisioned Throughput providing reserved capacity and superior latency for critical production demand.
Match the serving option to the workload, from interactive agents to high-throughput business processes. That is the Foundry advantage: not just frontier intelligence, but the platform to put it to work. Teams can match each workload to the right model, deployment option, and controls, balancing capability, responsiveness, and cost as adoption grows.
By bringing these choices together on Azure, Foundry helps customers focus on delivering business value , with the operational foundation to move from a promising agent to production at scale. Our customers work in domains where getting an answer isn’t enough, it has to be the right answer, and it has to hold up to scrutiny. The latest Azure OpenAI frontier models reason through a problem in steps we can follow, which is what makes it viable for the research and compliance workflows our professionals depend on.
Building on Microsoft Foundry lets us take those agentic workflows into production on infrastructure and services that already meet our governance, data residency, and security obligations. —Brian Diffin, CTO of Wolters Kluwer Tax & Accounting GPT-6 pricing and deployment options** Model Deployment Context Length Pricing (USD $/million tokens) Input Cached Input Cached Writes Output GPT-6 Astra Global Standard Short context $10.
00 $1. 00 $12. 50 $50.
00 Long context $20. 00 $2. 00 $25.
00 $75. 00 Data Zone Standard (US) Short context $11. 00 $1.
10 $13. 75 $55. 00 Long context $22.
00 $2. 20 $27. 50 $82.
50 Data Zone Standard (EU) Short context $12. 00 $1. 20 $15.
00 $60. 00 Long context $24. 00 $2.
40 $30. 00 $90. 00 GPT-6 Sol Global Standard Short context $2.
00 $0. 20 $2. 50 $10.
00 Long context $4. 00 $0. 40 $5.
00 $15. 00 Data Zone Standard (US) Short context $2. 20 $0.
22 $2. 75 $11. 00 Long context $4.
40 $0. 44 $5. 50 $16.
Originally published at azure.microsoft.com
