The short version
For most business agents, either API will work. Both offer reliable tool calling, schema-constrained outputs, streaming, batch discounts, prompt caching and a default of not training on API data. The choice usually comes down to three things: what the agent spends most of its time doing, where your company already runs its cloud, and which hosted features would save you build time.
Lumeor builds on both, and many of our systems call more than one model. Treat this as a choice per agent, not a company-wide allegiance.
Where the OpenAI API wins
Hosted building blocks. The Responses API bundles web search, file search with hosted vector stores, a code interpreter and remote MCP tools. For a simple document Q&A agent, hosted file search can replace a retrieval stack you would otherwise build and run.
Real-time voice. The Realtime API takes audio in and returns audio out from one model, which keeps latency low and makes interruptions feel natural. For phone and voice agents, that is a real advantage. Our AI voice agent guide and voice calling platform cover how those systems are put together.
Images and speech in one account. The OpenAI API also generates images and converts text to speech and speech to text. The Claude API returns text only, so a product that needs those features would add another vendor.
Agents SDK. The OpenAI Agents SDK gives a light structure for handoffs between agents, input and output guardrails, and built-in tracing.
Where the Claude API wins
Long context. Current Claude models accept up to 1M tokens of context. Agents that review contracts, reconcile large exports or work across a whole codebase can often load what they need directly instead of chunking it.
Long-running agent work. Claude models are widely used for coding and multi-step agent tasks. The Claude Agent SDK packages the same harness that runs Claude Code, with file, shell and web tools, so you can build an agent that works in a sandbox without writing the loop. Managed Agents, currently in beta, goes a step further and hosts both the loop and the sandbox. Our OpenAI Agents SDK vs Claude Agent SDK page compares the two SDKs in detail.
Prompt caching. Agents resend the same system prompt and tool definitions on every turn. Claude’s prompt caching makes those repeated tokens much cheaper and faster, which adds up quickly for busy agents.
Multi-cloud access. Claude runs on Amazon Bedrock, Google Cloud and Microsoft Foundry as well as Anthropic’s own API. OpenAI’s GPT models are now on Azure and Amazon Bedrock too, so check current availability in your cloud, but Claude covers all three major clouds. If procurement, data handling or credits already live in one of those clouds, that can decide the question.
What we recommend
Start from the job. For a voice agent, begin with OpenAI’s Realtime API and compare against a Claude pipeline if reasoning quality is the bottleneck. For document-heavy or long-running agents, begin with Claude. For everything else, run the same 30 to 50 real test cases through both providers at two price tiers and compare accuracy, latency and cost per completed task.
Whichever you pick, keep the model behind a thin interface in your own code, with prompts and test cases in version control. That makes a later switch, or a mixed setup with different models per step, a configuration change rather than a rebuild. To estimate the ongoing bill, see what it costs to run an AI agent each month.