GPU Inference Expands Into Sandboxes

Sandboxing is turning GPU inference into a broader agent infrastructure market. Once an AI agent needs to run Python, open files, browse the web, or keep a long running workspace alive, the winner is not just the cheapest model host. It is the platform that can pair model calls with safe, stateful execution. That is why inference vendors are moving toward the turf E2B and Daytona started on, and why Baseten is adding Sandboxes beside model serving and hosted tools.1 2 3 4 5 6

• The product overlap is concrete. Modal exposes Sandboxes with shared images and persistent volumes, and now offers both gVisor and VM runtimes. Daytona sells isolated sandboxes with file systems, process execution, desktop automation, and long lived sessions for coding agents. E2B packages the same core job as cloud computers for agents that run code, use browsers, and work with files.2 3 4 5
• The reason GPU platforms are pushing here is bundling. A customer building an agent often needs inference, then code execution, then another model call, all in one loop. If that full loop stays on one platform, the vendor captures more spend and becomes harder to replace. Modal already scaled Sandboxes to $300M annualized by October 2026, showing this is becoming a major revenue line, not a side feature.1 2
• The competitive lines are blurring in both directions. Modal, RunPod, Fireworks, and Baseten are moving from model serving into execution environments, while Daytona is publishing guides for running Fireworks based coding agents inside its sandboxes. That means the market is converging on a full stack agent runtime where inference and execution are sold together, even when they begin as separate products.1 5 6 7

The next phase is a stack battle around agent runtime ownership. Baseten, Modal, RunPod, and Fireworks are positioned to fold sandboxes into existing inference workflows, while specialists like E2B and Daytona will keep pushing deeper on isolation, persistence, and agent specific tooling. Over time, customers will buy fewer point products and more combined inference plus execution platforms.1 5 6 7