Comparativa cloud GPU · abril 2026
Mejor hosting cloud GPU — 10 proveedores comparados
Hemos probado y tarifado 10 proveedores de cloud GPU para que no pagues de más. Desde GPUs comunitarias a 0,10 $/h hasta clústeres H100 enterprise a 4+ $/h.
Los 10 proveedores
Tabla comparativa cloud GPU
Ordenado por valoración. Haz clic en cualquier proveedor para ver los detalles completos.
| Proveedor | Valoración | Precio inicial | GPUs principales | Destacados | Acción |
|---|---|---|---|---|---|
| RunPod Elección del editor | ★★★★★ | from $0.16/h | RTX A5000, RTX 3090 ≤80GB |
| Ver precios |
| Lambda Labs Elección del editor | ★★★★★ | from $0.69/h | Quadro RTX 6000, A100 40GB ≤80GB |
| Ver precios |
| CoreWeave | ★★★★☆ | from $1.25/h | L40S, H100 SXM ≤80GB |
| Ver precios |
| Paperspace | ★★★★☆ | from $0.45/h | A100, A6000 ≤80GB |
| Ver precios |
| Google Cloud GPU | ★★★★☆ | from $3.67/h | A100 40GB, A100 80GB ≤80GB |
| Ver precios |
| Hetzner GPU | ★★★★☆ | from €0.35/h | RTX 4000 SFF Ada, RTX PRO 6000 ≤96GB |
| Ver precios |
| AWS GPU (EC2) | ★★★★☆ | from $0.526/h | T4, A100 ≤80GB |
| Ver precios |
| Vast.ai Elección del editor | ★★★★☆ | from $0.10/h | RTX 3090, RTX 4090 ≤80GB |
| Ver precios |
| Azure GPU (NC T4/A100) | ★★★★☆ | from $0.526/h | T4, A100 ≤80GB |
| Ver precios |
| OVH GPU | ★★★★☆ | from €0.45/h | T4, V100 ≤80GB |
| Ver precios |
Reseñas detalladas de proveedores
Análisis en profundidad de cada cloud GPU con pros, contras y mejores escenarios.
RunPod Elección del editor
Best value GPU cloud — huge selection, community + secure cloud
- Cheapest community GPUs from $0.16/h
- Massive GPU variety including H100
- Serverless endpoints for inference APIs
- Great UI and pod management
- Community cloud less reliable than dedicated
- Storage costs add up over time
- Support can be slow on free tier
Lambda Labs Elección del editor
On-demand H100 clusters — developer-favourite for serious ML
- Reliable on-demand H100 availability
- No complex setup — SSH ready in seconds
- Lambda Stack saves setup time
- Competitive pricing vs hyperscalers
- Limited GPU types vs RunPod
- Fewer EU datacenter options
- No serverless endpoints
Vast.ai Elección del editor
Cheapest GPU cloud — peer-to-peer marketplace for budget training
- Absolute cheapest GPU compute available
- Widest GPU variety including consumer cards
- Good for fault-tolerant batch jobs
- Marketplace competition drives prices down
- Hosts can take instances offline anytime
- Variable reliability across providers
- Less suitable for time-sensitive inference
Paperspace
Gradient notebooks + GPU VMs — great for ML teams
- Best notebook experience of any cloud GPU
- Team collaboration features built-in
- Free tier with limited GPU hours
- Good documentation and tutorials
- Pricier than RunPod for raw compute
- Limited GPU types vs competitors
- Gradient platform has occasional issues
CoreWeave
Enterprise GPU clusters — Kubernetes-native with H100 & L40S
- Best multi-node GPU cluster performance
- High-speed InfiniBand interconnects
- Purpose-built for AI workloads
- Strong enterprise support
- Enterprise contracts required for large clusters
- Requires Kubernetes knowledge
- Sales-led process for large deployments
Hetzner GPU
Affordable EU GPU cloud — RTX 4000 Ada at European prices
- Best GPU pricing in Europe
- GDPR and EU data residency compliant
- Excellent API and automation support
- Trusted Hetzner infrastructure
- Limited GPU types — no H100 or A100
- Smaller VRAM vs US hyperscaler options
- Fewer GPU locations than US providers
OVH GPU
European GPU cloud with NVIDIA T4 and V100 options
- Strong EU data sovereignty guarantees
- Established cloud provider with SLA
- Multi-region EU availability
- Good for government/regulated industries
- Older GPU lineup (V100 still prominent)
- More complex setup vs RunPod
- Higher prices than Hetzner for GPU
Google Cloud GPU
TPU + GPU powerhouse — best ecosystem for TensorFlow
- Best TPU availability for TF workloads
- Deep Vertex AI + BigQuery integration
- Global infrastructure and reliability
- Preemptible instances cut costs significantly
- Expensive on-demand pricing
- Complex billing — easy to overspend
- Steep learning curve for GCP newcomers
AWS GPU (EC2)
Largest GPU fleet worldwide — T4 entry, P4/P5 for enterprise
- Most comprehensive ML toolchain (SageMaker)
- Spot instances for massive cost savings
- Best compliance certifications globally
- Inferentia for cost-effective inference
- A100/H100 on-demand pricing is very high
- Complex pricing model
- Not beginner-friendly for pure GPU rental
Azure GPU (NC T4/A100)
Microsoft's GPU cloud — T4 entry, best for Azure ML and enterprise AI
- Deep OpenAI / Azure OpenAI integration
- Best choice for Microsoft-stack enterprises
- Strong compliance and government certifications
- Azure ML Studio for no-code ML
- A100/H100 on-demand pricing is very high
- Complex portal and billing
- Vendor lock-in with Azure ecosystem
Preguntas frecuentes
¿Cuál es el cloud GPU más barato en 2026?
Vast.ai es el cloud GPU más barato desde 0,10 $/h para instancias comunitarias. RunPod es el mejor equilibrio precio/fiabilidad desde 0,16 $/h (RTX A5000 Community Cloud).
¿RunPod es lo bastante fiable para producción?
El Secure Cloud de RunPod es fiable para producción con hardware dedicado de datacenter. Community Cloud es más barato pero los hosts pueden retirar instancias. Para inferencia continua, usa Secure Cloud o Lambda Labs.
¿Qué cloud GPU tiene H100 disponibles?
Lambda Labs, CoreWeave, RunPod, AWS (p5) y Google Cloud ofrecen acceso a H100. CoreWeave tiene el mayor inventario de clústeres H100. Precios desde ~2 $/h (Lambda) hasta 4+ $/h (AWS on-demand).
¿Usar AWS/GCP/Azure o un cloud GPU especializado?
Para compute GPU puro, los especializados (RunPod, Lambda, Vast.ai) son 2–5× más baratos que los hyperscalers. Usa AWS/GCP/Azure solo si necesitas integración ML estrecha (SageMaker, Vertex AI) o compliance enterprise estricto.
¿Qué GPU necesito para fine-tunear Llama 3 70B?
Necesitas al menos una A100 80 GB, o 2× A100 40 GB en NVLink. Para Llama 3 8B, una RTX 3090/4090 24 GB es suficiente. RunPod es la mejor opción de calidad-precio para ambos.