6.1 Sol is now generally available on Amazon Bedrock, bringing stronger reasoning to coding, computer use, and professional workloads that run frequently
For an AI agent to complete a task, it may need to gather information, use tools, test different approaches, recover from errors, and verify its result. Every decision shapes what happens next. A wrong turn can add model interactions, tool calls, latency, and human intervention before the agent reaches a useful result.
The economics of an AI agent take shape across the entire task. Token prices influence the cost of each interaction, while reasoning quality influences how many interactions the work requires and whether they lead to a successful outcome. The total cost of completing a task depends on both.
generally available on Amazon Bedrock, running on an inference engine built for performance, security, and reliability at scale. A major upgrade to GPT-6 Sol, it delivers strong performance on agentic coding, computer use, and professional work. According to OpenAI, it brings near-Astra intelligence to everyday workflows.
Apply stronger reasoning across agentic work
Software engineering shows how reasoning quality affects an entire workflow. An agent may need to understand an unfamiliar repository, trace dependencies, determine where to make a change, and validate the implementation. According to OpenAI, GPT-6.1 Sol matches GPT-6 Astra on DeepSWE v1.1 at roughly one-fifth the cost per task. It also exceeds the best score from GPT-6 Sol by 6.4 percentage points while using a lower reasoning effort than that GPT-6 Sol result.
Codex puts that reasoning to work across the full development cycle. You can configure Codex to use GPT-6.1 Sol on Amazon Bedrock for work spanning investigation, implementation, and testing. Codex works with repositories, local files, terminals, and development tools to write features, fix bugs, and run tests. You can access Codex through the desktop app, CLI, and supported IDEs. For AWS development, the Agent Toolkit for AWS connects Codex to AWS documentation, APIs, and services through a single terminal command.
Turn information into action across documents and tools
The same reasoning capabilities apply when agents must interpret complex documents, select the appropriate tools, and adapt as conditions change. According to OpenAI, GPT-6.1 Sol approaches GPT-6 Astra on complex document analysis and improves on GPT-6 Sol when completing multistep workflows across business tools.
You can apply these capabilities through ready-to-use experiences or applications you build. In the desktop app, ChatGPT Work can gather information across files and applications and turn it into finished deliverables. Using supported Amazon Bedrock APIs, you can also build internal tools that synthesize documents, agents that coordinate work across systems, and customer-facing applications that evaluate multiple inputs.
Recognize limitations and respect constraints
Working effectively across tools also requires an agent to recognize when a tool has failed, an action is restricted, or information is missing. Communicating these limitations allows the application or user to intervene before the agent continues with incomplete information or takes an unintended action. According to OpenAI, GPT-6.1 Sol improves on GPT-6 Sol in challenging evaluations of transparency, user intent, and explicit restrictions.
When building with supported Amazon Bedrock APIs, you can define the tools available to the model. You can also determine how your application responds when an action requires approval or cannot be completed. These application-level controls complement the model improvements by helping you keep people involved when a workflow reaches a consequential decision.
Run GPT-6.1 Sol on Amazon Bedrock
Amazon Bedrock provides the infrastructure and controls to run GPT-6.1 Sol in production. You can govern model access through AWS Identity and Access Management (IAM) policies and audit invocations through AWS CloudTrail. To help keep traffic within your network boundaries, you can use virtual private cloud (VPC) endpoints powered by AWS PrivateLink. Inference runs on hardware-isolated infrastructure with zero-operator access, so not even AWS operators can access your prompts and completions during inference.
Your inference data isn’t used for model training, and using GPT-6.1 Sol doesn’t require you to opt into sharing your data with OpenAI. For automated abuse detection, classifier-flagged traffic is retained by AWS for up to 30 days and processed programmatically. You can request zero data retention through your AWS account team. See data retention for details.
Get started
GPT-6.1 Sol brings stronger reasoning to agentic work at a fraction of the cost per task, so your agents reach the right answer in fewer steps. You can get started with GPT-6.1 Sol in the Amazon Bedrock console or programmatically through supported Amazon Bedrock APIs. For information about supported AWS Regions, endpoints, APIs, features, inference profiles and pricing, see the Amazon Bedrock documentation.
Interested in how Amazon Bedrock can support your team?Connect with us to start the conversation.
