AWS vs GCP vs Azure: Perbandingan Harga GPU AI 2026
AWS p5, GCP A3, Azure ND H100 v5 — perbandingan harga GPU hyperscaler 2026. On-demand, spot, reserved, dan kapan tiap cloud menang.
Tiga hyperscaler besar menawarkan H100 GPU dalam range $11-13/jam sama untuk workload AI 2026. Perbedaan di harga spot, integrasi ekosistem, dan kemudahan akses kapasitas reserved. Untuk harga real-time 12 provider GPU, GPU Pricing Calculator.
Berapa setiap hyperscaler charge untuk H100 2026?
H100 SXM5 80GB per-GPU di region us-east-1 equivalent:
| Cloud | Instance | On-demand | Spot | Reserved (1yr) |
|---|---|---|---|---|
| AWS | p5.48xlarge | $12.29 | $6.40 | $7.50 |
| GCP | A3 (a3-highgpu-8g) | $11.06 | $5.50 | $7.20 |
| Azure | ND H100 v5 | $12.96 | $6.80 | $8.00 |
| AWS | p5e.48xlarge (H200) | $14.25 | $7.40 | $8.60 |
| GCP | A3 Ultra (H200) | $13.40 | $7.00 | $8.50 |
Cloud GPU non-hyperscaler:
| Provider | H100 SXM on-demand |
|---|---|
| Hyperbolic | $1.49 |
| RunPod Community | $1.99 |
| Vast.ai | $2.40 |
| RunPod Secure | $2.99 |
| Lambda Labs | $2.99 |
| GCP (hyperscaler termurah) | $11.06 |
| AWS | $12.29 |
| Azure | $12.96 |
Gap 6-8×. Non-hyperscaler charge kurang karena tidak bundle networking enterprise, IAM, redundansi regional.
Kapan AWS masuk akal?
- Model managed Bedrock: Claude, Llama, Nova dengan provisioned throughput
- Compliance enterprise: HIPAA, FedRAMP, SOC 2
- Data existing di S3
- Custom Model Import
Pain points: p5 minimum 8-GPU ($98/jam), reserved 1-tahun commit, spot fluctuates.
Kapan GCP masuk akal?
- AI Studio + Vertex AI integration
- TPUs kompetitif vs H100
- A3 Ultra (cluster H200)
- Multi-region serving
Pain points: 8-GPU minimum, preemptible lebih pendek, markup Vertex 30-50%.
Kapan Azure masuk akal?
- OpenAI Service integration
- Microsoft 365 + Copilot ekosistem
- Sales enterprise fleksibel
- Partnership Mistral, Cohere
Pain points: ND H100 v5 supply-constrained, Low Priority kapasitas rendah.
Bagaimana dengan fee egress cross-cloud?
| Source | Destination | $/GB |
|---|---|---|
| AWS → Internet | $0.05-0.09 | |
| AWS → GCP | $0.08 | |
| GCP → Internet | $0.08-0.12 | |
| Azure → Internet | $0.05-0.08 |
Inference streaming 1KB responses: ~$0.27/bulan trivial. Audio/video outputs: bisa $2,700/bulan signifikan.
Tagihan hyperscaler termurah untuk workload AI tipikal?
Workload 1: B2B SaaS chatbot, 100k requests/hari, AWS
GPU (Bedrock Sonnet 4.6): ~$1,500/bulan
S3: $1, Egress 1TB: $90, Lambda: $50
Total: ~$1,641/bulan
Vs RunPod self-hosted Llama 4 70B: $4,355/bulan. Hyperscaler menang untuk managed inference.
Workload 2: Fine-tuning 70B from scratch, GCP
8× H100 SXM × 100 jam = $11,060
Spot: $5,500 dengan checkpointing
Total: ~$5,800
vs RunPod: ~$2,700. Cloud khusus menang 2-3× untuk training.
Workload 3: Inference 24/7 (10M req/hari)
Butuh contract enterprise custom.
Arsitektur tepat untuk 2026
- Storage di cloud primary
- Inference high-volume via API managed. Pay-per-token menang di bawah ~500M token/bulan.
- Inference custom atau >500M token/bulan di RunPod, Together, Fireworks. Hemat 4-8×.
- Training/fine-tuning di Crusoe, Lambda Labs, CoreWeave. Hemat 2-3×.
- Egress paths diminimalisasi via region-local.
Pajak hyperscaler nyata tapi worth it ketika benar-benar butuh ekosistem mereka.