Modal vs Fly.io
Agent-native side-by-side. Scores are curated estimates on a 0–10 scale. Lock-in: higher = worse. Prefer JTBD picks via /api/decide when choosing for a job.
| Dimension | Modal | Fly.io |
|---|---|---|
| Overall | 8.4 | 8.3 |
| Capability fit | 9.0 | 8.8 |
| Price / performance | 8.2 | 8.2 |
| Latency / reliability | 8.6 | 8.0 |
| Developer & agent DX | 9.6 | 8.8 |
| Privacy / data retention | 7.8 | 7.8 |
| Lock-in risk (higher = worse) | 4.5 | 3.5 |
| Maturity / track record | 8.2 | 8.5 |
| Pricing | As of 2026-10-24 (modal.com/pricing, fetched 2026-10-24): Python-native serverless GPU/CPU billed per second of compute ('You never pay for idle resources'). GPU list rates per second: H100 SXM5 '$0.001097', H200 SXM '$0… | Pay for machines/volumes/bandwidth; Firecracker VMs; scale-to-zero; Machines API for agents. |
| Tagline | Depot darling for Python agent backends and bursty GPU jobs. If you think in functions not VMs, start here. | Excellent for globally distributed agent sidecars and Machines-based sandboxes. Prefer Railway/Render if you… |
Modal
Depot darling for Python agent backends and bursty GPU jobs. If you think in functions not VMs, start here. Strengths: Best-in-class Python DX for serverless compute; GPUs + sandboxes + cron in one model; Scale-to-zero economics.
Strengths
- Best-in-class Python DX for serverless compute
- GPUs + sandboxes + cron in one model
- Scale-to-zero economics
Weaknesses
- Premium vs raw RunPod $/GPU-sec sometimes
- Python-centric (polyglot harder)
- Less classic VM control
Fly.io
Excellent for globally distributed agent sidecars and Machines-based sandboxes. Prefer Railway/Render if you want less infra thinking. Strengths: Global edge VMs close to users; Machines API great for ephemeral agent workloads; WireGuard private networking.
Strengths
- Global edge VMs close to users
- Machines API great for ephemeral agent workloads
- WireGuard private networking
Weaknesses
- Ops complexity vs PaaS
- Support historically uneven
- Pricing surprises on egress/volumes
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