Best Infrastructure Platforms for Coding Agents in 2026
Modal's engineering team surveys seven infrastructure platforms purpose-built for running coding agents at scale. The thesis: general-purpose cloud (AWS/GCP/Azure) is the wrong substrate for agent workloads — specialized platforms eliminate cluster management, reservations, and idle capacity overhead. The article positions Modal as the leader, but the comparative landscape data is useful regardless of vendor.
Seven Platforms Surveyed
1. Modal
Serverless compute with on-demand GPU access. gVisor container isolation, scale-to-zero architecture, Python/TypeScript/Go SDKs, GPU options from T4 through B200/B200+. SOC 2 Type II and HIPAA-compliant. Claims 50,000+ concurrent sandbox sessions, 10,000+ teams including Ramp, Lovable, and Applied Compute.
2. E2B
Firecracker microVM isolation for ephemeral code execution. Open-source option for self-hosting. Supports up to 1,100 concurrent sandboxes on higher-tier plans. CPU-focused, no GPU acceleration.
3. Daytona
Persistent development environments using Sysbox-based container isolation. Configurable runtime persistence and Docker/OCI compatibility. Open-source with ~72.2k GitHub stars. For teams needing workspace continuity.
4. Blaxel
Persistent "agent computers" that stay on standby and resume quickly. Sandboxed compute runtimes with REST API and MCP server access, template support, volumes for storage that survives sandbox destruction.
5. Together Code Sandbox
Configurable VM-based development environments with snapshotting. Separate Code Interpreter product for sandboxed Python execution via API.
6. Vercel Sandbox
Ephemeral Linux microVMs powered by Firecracker, with sudo access, package managers, and automatic state persistence. Priced around active CPU time. For secure ephemeral execution rather than GPU access.
7. Cloudflare Sandbox
Python and Node.js execution through a TypeScript-first SDK. Isolated filesystem with configurable keepAlive and sleep behavior. Tutorials include an AI code executor and AI coding agent built with the OpenAI Agents SDK.
Key Claims
- CPU-based execution is the primary sandbox workload — coding agents mostly run generated code in secure CPU sandboxes
- GPU access is on-demand when needed, not the default
- GPU memory snapshots can reduce cold starts by up to ~10x for some workloads
- Sync Labs achieves "95 deployments per day" using Modal's no-YAML approach
- Suno achieved 4-month time-to-market acceleration by avoiding custom infrastructure