Comparativa cloud GPU · abril 2026
Mejor hosting cloud GPU — 20 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.
Algunos enlaces son de afiliados — recibimos una comisión sin coste extra para ti. Precios verificados abril 2026. Comprueba siempre el sitio del proveedor para precios actuales.
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Los 20 proveedores
Tabla comparativa cloud GPU
Ordenado por valoración. Haz clic en cualquier proveedor para ver los detalles completos.
¿Inferencia puntual en lugar de entrenamiento? Compara las plataformas GPU serverless — facturación por segundo y escalado a cero. ¿No sabes qué GPU necesitas? Prueba el GPU Finder.
| 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 |
| Nebius Elección del editor | ★★★★★ | from $1.55/h | H100, H200 ≤192GB |
| Ver precios |
| CoreWeave | ★★★★☆ | from $6.50/h | L40S, H100 SXM ≤80GB |
| Ver precios |
| Paperspace | ★★★★☆ | from $0.45/h | A100, A6000 ≤80GB |
| Ver precios |
| Google Cloud GPU | ★★★★☆ | from $0.71/h | A100 40GB, A100 80GB ≤80GB |
| Ver precios |
| Together AI | ★★★★☆ | from $3.99/h | H100, H200 ≤141GB |
| Ver precios |
| Jarvis Labs | ★★★★☆ | from $0.41/h | A30, L4 ≤80GB |
| Ver precios |
| Hetzner GPU | ★★★★☆ | from €1.42/h | RTX 4000 SFF Ada, RTX PRO 6000 ≤80GB |
| Ver precios |
| AWS GPU (EC2) | ★★★★☆ | from $0.53/h | A100, H100 ≤80GB |
| Ver precios |
| Crusoe | ★★★★☆ | from $1.50/h | H100, H200 ≤192GB |
| Ver precios |
| TensorDock | ★★★★☆ | from $0.10/h | RTX 4090, RTX 3090 ≤80GB |
| Ver precios |
| Lyceum Elección del editor | ★★★★☆ | from $1.19/h | A100 80GB, H100 ≤141GB |
| Ver precios |
| Vast.ai Elección del editor | ★★★★☆ | from $0.02/h | RTX 3090, RTX 4090 ≤80GB |
| Ver precios |
| Azure GPU (NCv3/NDA) | ★★★★☆ | from $0.53/h | A100, H100 ≤80GB |
| Ver precios |
| Hyperstack | ★★★★☆ | from $0.15/h | RTX A4000, RTX A6000 ≤80GB |
| Ver precios |
| Massed Compute | ★★★★☆ | from $0.35/h | RTX A6000, A40 ≤80GB |
| Ver precios |
| Scaleway | ★★★★☆ | from €0.79/h | L4, L40S ≤80GB |
| Ver precios |
| OVH GPU | ★★★★☆ | from €0.36/h | T4, V100 ≤80GB |
| Ver precios |
| Salad | ★★★★☆ | from $0.02/h | RTX 3090, RTX 4090 ≤24GB |
| Ver precios |
Reseñas detalladas de proveedores
Análisis en profundidad de cada cloud GPU con pros, contras y mejores escenarios.
#1
RunPod Elección del editor
Best value GPU cloud — huge selection, community + secure cloud
Mejor calidad-precio RTX A5000RTX 3090RTX 4090RTX A6000L40SA100 80GBH100H200B200 hasta 80 GB VRAM
Pros
- Cheapest community GPUs from $0.16/h
- Massive GPU variety including H100
- Serverless endpoints for inference APIs
- Great UI and pod management
Contras
- Community cloud less reliable than dedicated
- Storage costs add up over time
- Support can be slow on free tier
Ideal para: Fine-tuning LLMsStable DiffusionTrainingInference
#2
Lambda Labs Elección del editor
On-demand H100 clusters — developer-favourite for serious ML
Enterprise Quadro RTX 6000A100 40GBA100 80GBH100A10 hasta 80 GB VRAM
Pros
- Reliable on-demand H100 availability
- No complex setup — SSH ready in seconds
- Lambda Stack saves setup time
- Competitive pricing vs hyperscalers
Contras
- Limited GPU types vs RunPod
- Fewer EU datacenter options
- No serverless endpoints
Ideal para: LLM trainingResearchFine-tuningMulti-GPU jobs
#3
Vast.ai Elección del editor
Cheapest GPU cloud — peer-to-peer marketplace for budget training
Económico RTX 3090RTX 4090A100H100RTX 3060 hasta 80 GB VRAM
Pros
- Absolute cheapest GPU compute available
- Widest GPU variety including consumer cards
- Good for fault-tolerant batch jobs
- Marketplace competition drives prices down
Contras
- Hosts can take instances offline anytime
- Variable reliability across providers
- Less suitable for time-sensitive inference
Ideal para: Batch trainingBudget experimentsStable DiffusionData processing
#4
Paperspace
Gradient notebooks + GPU VMs — great for ML teams
Notebooks A100A6000RTX 4000V100 hasta 80 GB VRAM
Pros
- Best notebook experience of any cloud GPU
- Team collaboration features built-in
- Free tier with limited GPU hours
- Good documentation and tutorials
Contras
- Pricier than RunPod for raw compute
- Limited GPU types vs competitors
- Gradient platform has occasional issues
Ideal para: NotebooksML teamsPrototypingEducation
#5
CoreWeave
Enterprise H100 clusters — Kubernetes-native GPU cloud
Enterprise L40SH100 SXMA100 SXMA40 hasta 80 GB VRAM
Pros
- Best multi-node GPU cluster performance
- High-speed InfiniBand interconnects
- Purpose-built for AI workloads
- Strong enterprise support
Contras
- Expensive — not for hobbyists
- Requires Kubernetes knowledge
- Sales-led process for large clusters
Ideal para: Large-scale trainingFoundation modelsEnterprise AIMulti-node jobs
#6
Hetzner GPU
EU-sovereign dedicated GPU servers — RTX PRO 6000 Blackwell 96GB
eu-sovereign RTX 4000 SFF AdaRTX PRO 6000 hasta 80 GB VRAM
Pros
- 96GB VRAM on a single card
- EU jurisdiction and euro invoicing
- Dedicated hardware nobody else shares
- No minimum term, immediate cancellation
Contras
- Not the cheap option — €1.42/h vs €0.36/h at OVH
- Only two SKUs, one currently out of stock
- No A100, no H100, no SXM datacenter parts
- Monthly servers, not per-hour cloud VMs
Ideal para: EU complianceDedicated hardwareLarge-VRAM single-card workLong-running workloads
#7
OVH GPU
European GPU cloud with NVIDIA T4 and V100 options
Enterprise T4V100A100 hasta 80 GB VRAM
Pros
- Strong EU data sovereignty guarantees
- Established cloud provider with SLA
- Multi-region EU availability
- Good for government/regulated industries
Contras
- Older GPU lineup (V100 still prominent)
- More complex setup vs RunPod
- Higher prices than Hetzner for GPU
Ideal para: EU projectsInferenceModerate trainingGDPR requirements
#8
Google Cloud GPU
TPU + GPU powerhouse — best ecosystem for TensorFlow
Hyperscaler A100 40GBA100 80GBH100T4L4 hasta 80 GB VRAM
Pros
- Best TPU availability for TF workloads
- Deep Vertex AI + BigQuery integration
- Global infrastructure and reliability
- Preemptible instances cut costs significantly
Contras
- Expensive on-demand pricing
- Complex billing — easy to overspend
- Steep learning curve for GCP newcomers
Ideal para: TensorFlow workloadsTPU trainingEnterprise AIVertex AI pipelines
#9
AWS GPU (EC2)
Largest GPU fleet worldwide — P4/P5 instances for enterprise
Hyperscaler A100H100V100T4Inferentia2 hasta 80 GB VRAM
Pros
- Most comprehensive ML toolchain (SageMaker)
- Spot instances for massive cost savings
- Best compliance certifications globally
- Inferentia for cost-effective inference
Contras
- Most expensive on-demand GPU pricing
- Complex pricing model
- Not beginner-friendly for pure GPU rental
Ideal para: Enterprise MLOpsSageMaker pipelinesProduction inferenceRegulated industries
#10
Azure GPU (NCv3/NDA)
Microsoft's GPU cloud — best for Azure ML and enterprise AI
Hyperscaler A100H100V100T4 hasta 80 GB VRAM
Pros
- Deep OpenAI / Azure OpenAI integration
- Best choice for Microsoft-stack enterprises
- Strong compliance and government certifications
- Azure ML Studio for no-code ML
Contras
- High on-demand pricing
- Complex portal and billing
- Vendor lock-in with Azure ecosystem
Ideal para: Azure ML pipelinesMicrosoft stack AIEnterprise complianceOpenAI API users
#11
Crusoe
Climate-aligned GPU cloud — H100, H200, B200 and MI300X on green energy
specialist H100H200B200A100 80GBL40SMI300X hasta 192 GB VRAM
Pros
- H200 HGX at $4.29/h with InfiniBand multi-node
- B200 availability while most clouds wait-list
- InfiniBand 3.2 Tb interconnects for serious multi-node
- Climate-positive operations (uses flared methane)
Contras
- Smaller GPU variety than RunPod
- Region selection limited (mostly US + Iceland)
- Sales-led for large deployments
Ideal para: LLM training at scaleMulti-node H100/H200 jobsSustainable AI workloadsAMD MI300X clusters
#12
Nebius Elección del editor
EU-sovereign AI cloud from the Netherlands — full GDPR compliance, H100 to B200
eu-sovereign H100H200B200L40SA100 80GB hasta 192 GB VRAM
Pros
- Strong EU data residency — perfect for German / EU enterprise
- Modern hardware including B200 SXM
- Managed cluster orchestration included
- Strong customer support in European hours
Contras
- More expensive on-demand than RunPod / Vast.ai
- EU-only regions (no US datacenters)
- Smaller global presence than hyperscalers
Ideal para: EU-sovereign AI workloadsGDPR-bound enterprisesFrontier model trainingEuropean startups
#13
Together AI
Inference-first GPU cloud — H100/H200 with optimized serving stacks
specialist H100H200A100 80GBL40S hasta 141 GB VRAM
Pros
- Best-in-class inference performance
- Excellent open-source model coverage
- Strong fine-tuning workflow
- Token-based pricing for variable load
Contras
- Less GPU variety than RunPod
- Focus is inference, not raw training
- Custom interconnects not exposed
Ideal para: High-throughput inferenceOpen-source LLM servingLlama / Mistral fine-tuningProduction AI APIs
#14
Hyperstack
Global GPU cloud specialist — RTX A4000 from $0.15/h, plus H100, H200 and B200
specialist RTX A4000RTX A6000L40A100 80GBH100H200B200B300 hasta 80 GB VRAM
Pros
- Outstanding entry pricing for A6000
- Full networking stack (VPC, firewall, NAT)
- UK / EU regions for European latency
- Reservation discount up to 75%
Contras
- No B200 / H200 yet (April 2026)
- Smaller marketing footprint than RunPod
- Limited template marketplace
Ideal para: Budget training jobsStable Diffusion at scaleVPC-isolated workloadsEU-friendly compute
#15
TensorDock
Marketplace GPU cloud — RTX A4000 from $0.10/h, RTX 4090 $0.35/h, H100 SXM5 $2.25/h
marketplace RTX 4090RTX 3090A100 80GBH100L40S hasta 80 GB VRAM
Pros
- Among the cheapest H100 access in 2026
- Wide host network = better availability
- Per-second billing for short jobs
- Free egress saves on data-heavy workloads
Contras
- Reliability varies by host
- No managed cluster orchestration
- Support is community-led
Ideal para: Budget GPU rentalsStable Diffusion fine-tuningShort-burst trainingIndie ML developers
#16
Salad
Distributed inference cloud — RTX 3090 $0.09/h, RTX 4090 $0.16/h
inference-budget RTX 3090RTX 4090RTX 3080RTX 3070 hasta 24 GB VRAM
Pros
- Cheapest consumer GPUs — RTX 3090 from $0.09/h
- Massive horizontal scale (1000+ nodes)
- Auto-fleet management for inference
- No data-egress charges
Contras
- Distributed = no persistent storage
- Not suitable for training
- Latency varies by node geography
Ideal para: Stateless inferenceStable Diffusion bulk generationEmbedding generationCost-sensitive batch jobs
#17
Jarvis Labs
On-demand A30 / A100 / H100 from $0.41/h
specialist A30L4A100 40GBA100 80GBRTX Pro 6000H100H200 hasta 80 GB VRAM
Pros
- A30 from $0.41/h, A100 40GB from $0.89/h
- RTX Pro 6000 Blackwell — 96GB on a single card
- Polished UI for non-DevOps users
- Quick spinup, low friction
Contras
- Smaller GPU variety than RunPod
- No serverless / autoscaling
- Limited European presence
Ideal para: Researchers and indie developersLlama fine-tuningStable Diffusion trainingJupyter notebook users
#18
Lyceum Elección del editor
EU-sovereign AI cloud — H100 to H200 with full data residency
eu-sovereign A100 80GBH100H200L40S hasta 141 GB VRAM
Pros
- Strong EU data residency (no US transit)
- H200 availability in Europe
- ISO 27001 + SOC 2 certifications
- European billing and contracts
Contras
- Smaller capacity than US-based clouds
- Higher base price than RunPod / Vast.ai
- Limited GPU variety beyond Nvidia
Ideal para: EU-regulated industriesGDPR-strict workloadsEuropean public sectorHealth and finance AI
#19
Massed Compute
Workstation-grade GPUs for AI/ML/VFX — A100 from $1.79/h
specialist RTX A6000A40A100 80GBH100RTX 6000 Ada hasta 80 GB VRAM
Pros
- Strong A6000 / A40 lineup at moderate price
- Pre-built VFX and AI templates
- RDP/VNC for visual workflows
- Per-second billing
Contras
- US-only datacenters
- No serverless inference
- Smaller community than RunPod
Ideal para: VFX and 3D renderingStable Diffusion fine-tuningWorkstation-style AI devMulti-tenant studios
#20
Scaleway
European cloud with H100 SXM and L40S — Paris and Amsterdam regions
eu-sovereign L4L40SH100H100 SXM hasta 80 GB VRAM
Pros
- Strong EU presence (Paris + Amsterdam)
- Mature cloud platform (S3, k8s, networking)
- Per-minute billing
- EUR pricing avoids USD volatility
Contras
- More expensive than US specialists like RunPod
- No B200 / H200 yet
- Limited capacity for big training runs
Ideal para: European startupsGDPR-compliant inferencek8s-based AI deploymentsEU enterprise
Preguntas frecuentes
¿Cuál es el cloud GPU más barato en 2026?
RunPod es el cloud GPU con mejor relación calidad-precio en 2026 — desde 0,16 $/h (RTX A5000 Community Cloud), con el mejor equilibrio precio/fiabilidad de los 20 proveedores que probamos, más endpoints Serverless y volúmenes persistentes. Si solo buscas el precio absoluto más bajo: Vast.ai desde 0,10 $/h (interrumpible).
¿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.