2025 GPU Cloud Showdown: Deep Dive on 10 Serverless Platforms
Nexmoe June 17, 2025
This article is an AI translation and may contain semantic inaccuracies.
| Rank | Provider | Pricing | Scalability | GPU Types | Ease of Use | Speed |
|---|---|---|---|---|---|---|
| 1 | Gongji Compute | Ultra‑low cost; RTX 4090 at 1.68 RMB/hour; per‑second billing | Elastic scaling; dynamic node adjustment | RTX 4090, RTX 5090, L40, H800 | Full API; Docker support; Jupyter environment | Seconds‑level cold start; 99.9% availability |
| 2 | RunPod | Low cost, per‑second billing | Auto‑scales across 9 regions; no hard concurrency limit | Wide range (T4 to A100/H100, incl. AMD) | Container‑based; REST API, SDK, quick templates | 48% of cold starts < 200ms |
| 3 | Capital | Mid‑range; free credits in entry plan | Scales quickly to hundreds; plans vary | Broad range from T4 to H100 | Python SDK with auto‑containerization | Ultra‑low latency (2–4s cold start) |
| 4 | Replicate | Higher cost for custom models; community models free | Auto‑scales but cold start can be long | T4, A40, A100, some H100 | Zero‑config prebuilt models; Cog for custom code | Custom model cold start can exceed 60s |
| 5 | Fal AI | Competitive pricing on high‑end GPUs | Scales to thousands; optimized for bursty generation | Focus on high‑end GPUs (A100, H100, A6000) | Ready‑to‑use APIs for diffusion models | Optimized cold start (few seconds) and fast inference |
| 6 | Baseten | Usage‑based (per‑minute billing) | Auto‑scaling with configurable replicas | T4, A10G, L4, A100/H100 options | Truss framework simplifies deploy; clean UI | 8–12s cold start; dynamic batching boosts throughput |
| 7 | AI news | Very affordable, usage‑based | Elastic scaling across 20+ locations | RTX 30/40 series, A100 SXM | One‑click JupyterLab; simple API | Fast instance startup; low network latency |
| 8 | Beam Cloud | One of the lowest prices; free tier | Auto‑scales from zero; dev‑friendly limits | T4, RTX 4090, A10G, A100/H100 | Python SDK, CLI, hot reload | Very fast (2–3s cold start) |
| 9 | Cerebrium | Competitive per‑second billing | Seamless scaling across GPU types | 12+ types incl. H100, A100, L40 | Minimal config; supports websockets and batching | Extremely fast cold start (2–4s) |
| 10 | Google Cloud Run | Usage‑based + extra CPU/memory costs | Scales from 0 to 1000 instances | NVIDIA L4 (24GB) for now | Container native; integrated in GCP | 4–6s cold start; near bare‑metal performance |
| 11 | Azure Container Apps | Expected to align with Azure pricing | Managed event‑driven scale (preview) | NVIDIA T4 and A100 (more options coming) | Simple YAML; Azure Monitor integration | ~5s cold start expected; full GPU performance when active |