AI tool comparison
Azure Foundry Hosted Agents vs Cua
Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.
Developer Tools
Azure Foundry Hosted Agents
Per-session isolated agent sandboxes on Azure — scale to zero, any framework
50%
Panel ship
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Community
Paid
Entry
Microsoft Azure's Foundry Agent Service now offers Hosted Agents in public preview — per-session isolated compute sandboxes purpose-built for running AI agents at scale. Each session gets its own container with a persistent filesystem, internet access (optional), and a Python environment pre-loaded with common agent dependencies. Sessions spin up in seconds and terminate — and stop billing — the moment the agent task completes. The design is framework-agnostic: it officially supports LangGraph, OpenAI Agents SDK, Claude Agent SDK, and Microsoft's own Agent Framework, with others planned. This removes one of the most awkward parts of deploying agents in production: figuring out where they actually run. The persistent filesystem per session means agents can read and write files across their task without external storage configuration. Pricing is $0.0994/vCPU-hour and $0.0118/GiB-hour — competitive with Lambda/Cloud Run for bursty workloads. The service is available in six Azure regions at launch. For enterprises already invested in Azure, this is a compelling "we just figured out the infra" moment. Independent developers can also use it without an enterprise agreement.
Developer Tools
Cua
Open-source infra for computer-use agents across Mac, Linux & Windows
75%
Panel ship
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Community
Paid
Entry
Cua is an open-source infrastructure toolkit for building, benchmarking, and deploying computer-use agents. It provides a unified environment where AI agents can control full desktops across macOS, Linux, and Windows — without stealing the user's cursor or disrupting their workflow. The project ships four components: Cua Driver (background automation for macOS apps), Cua Sandbox (a unified API for VM and container control), CuaBot (multi-agent CLI with native window integration), and Cua-Bench (a benchmark suite compatible with OSWorld and ScreenSpot). Lume, a VM manager optimized for Apple Silicon, rounds out the toolkit. With 15,000+ stars and an MIT license, Cua is quickly becoming the de facto standard for teams building autonomous computer-use pipelines. As agents graduate from chat to "just do the thing," infrastructure like Cua becomes load-bearing.
Reviewer scorecard
“Framework-agnostic hosted sandboxes with scale-to-zero is exactly what I need for deploying agents without maintaining my own Kubernetes cluster. The per-session isolation eliminates a whole class of security concerns I was handling manually. The Claude Agent SDK support means I don't have to choose between Azure and my preferred model.”
“Cua solves the hardest part of computer-use agents — getting a stable, reproducible environment that doesn't fight your OS. The background automation mode alone is worth it for devs building macOS agents. 15k stars in a short window is a strong signal.”
“Public preview means production instability risk and pricing could change significantly at GA. The cold start time for agent sessions needs to be benchmarked against real workloads before committing. And six regions is thin coverage for global deployments — wait for broader availability.”
“Computer-use agents are still fragile — they miss UI state changes, struggle with dynamic content, and hallucinate element positions. Cua gives you infrastructure, not reliability. Until benchmark scores improve on diverse real-world tasks, this is a research toy with impressive packaging.”
“The battle for agent infrastructure is the next cloud wars — and Microsoft just answered Google Cloud's agent platform launch with their own. Framework-agnostic compute that works with any model provider is a smart commoditization play: own the infrastructure layer, let the model battle play out above it.”
“Every agentic workflow that touches a UI needs something like Cua. As models improve at visual understanding and cursor control, this infrastructure layer will be what production computer-use runs on. It's early, but it's exactly the right early.”
“This is squarely developer infrastructure — not directly relevant to creative workflows unless your studio runs its own agents. Worth watching for the ecosystem tools that get built on top of it.”
“If you're building an AI that can use Figma, Photoshop, or any creative tool on your behalf, Cua is the missing scaffolding. The benchmarking suite means you can actually measure how well your agent handles design tasks — not just hope.”
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