The Hidden Costs of AWS GPU Instances
If you're running machine learning workloads, you've probably noticed that AWS GPU pricing is brutal. A single p5.48xlarge instance (8x H100) costs over $98/hour on-demand. That's $2,352/day or $70,560/month if running 24/7.
But the sticker price is just the beginning. Let's break down the real costs:
- Data transfer fees: $0.09/GB for data out (adds up fast with large models)
- Storage costs: EBS volumes for model weights, datasets
- Reserved instance lock-in: 1-3 year commitments for discounts
- Spot instance interruptions: Lost work when instances get reclaimed
Head-to-Head: AWS vs GPUBrazil Pricing
Let's compare apples to apples across different GPU configurations:
NVIDIA H100 80GB
| Provider | Configuration | Hourly Cost | Monthly (24/7) |
|---|---|---|---|
| AWS p5.48xlarge | 8x H100 | $98.32 | $70,790 |
| AWS (1yr Reserved) | 8x H100 | $62.00 | $44,640 |
| GPUBrazil FLEX | 8x H100 | $22.40 | $16,128 |
| GPUBrazil PREMIUM | 8x H100 | $28.00 | $20,160 |
Savings: 71-77% compared to AWS on-demand
NVIDIA A100 80GB
| Provider | Configuration | Hourly Cost | Monthly (24/7) |
|---|---|---|---|
| AWS p4d.24xlarge | 8x A100 | $32.77 | $23,594 |
| AWS (1yr Reserved) | 8x A100 | $20.73 | $14,926 |
| GPUBrazil FLEX | 8x A100 | $12.80 | $9,216 |
Savings: 61% compared to AWS on-demand
NVIDIA L40S
| Provider | Configuration | Hourly Cost | Monthly (24/7) |
|---|---|---|---|
| AWS g6.48xlarge | 8x L40S | $14.67 | $10,562 |
| GPUBrazil FLEX | 8x L40S | $7.20 | $5,184 |
Savings: 51% compared to AWS
💡 No Hidden Fees
GPUBrazil pricing is all-inclusive. No surprise charges for data transfer, no storage fees for reasonable usage, and no long-term commitments required.
Real-World Scenario: Training a LLM
Let's look at a realistic ML project: fine-tuning a 70B parameter model for 100 hours.
| Cost Component | AWS | GPUBrazil |
|---|---|---|
| Compute (8x H100, 100hrs) | $9,832 | $2,240 |
| Data Transfer (500GB) | $45 | $0 |
| Storage (2TB EBS) | $200 | Included |
| Total | $10,077 | $2,240 |
Total savings: $7,837 (78%) on a single training run!
Why is GPUBrazil So Much Cheaper?
We get this question a lot. Here's how we keep prices low:
- Direct datacenter partnerships: We work directly with GPU datacenters, cutting out middlemen
- Efficient infrastructure: Optimized for ML workloads, not general-purpose computing
- Lower margins: We believe GPU access should be affordable for everyone
- No enterprise sales overhead: Self-service platform means lower operational costs
When to Use AWS vs GPUBrazil
Choose AWS if:
- You need tight integration with other AWS services (S3, Lambda, etc.)
- Your company has existing AWS enterprise agreements
- You need specific compliance certifications (FedRAMP, etc.)
Choose GPUBrazil if:
- Cost is a primary concern (it usually is)
- You need flexible, on-demand GPU access
- You're running ML training or inference workloads
- You want simple, transparent pricing
- You're a startup, researcher, or indie developer
Start Saving 70%+ on GPU Costs Today
No commitments, no hidden fees. Pay only for what you use.
Get $5 Free Credit →Migration is Easy
Switching from AWS to GPUBrazil takes minutes:
- Sign up and add credits
- Launch an instance with your preferred GPU config
- SSH in (same as EC2)
- Install your ML framework (or use our pre-built images)
- Start training!
Our instances come with CUDA pre-installed, and we support all major ML frameworks: PyTorch, TensorFlow, JAX, and more.
Conclusion
For most ML workloads, AWS is simply overpriced. You're paying a premium for a brand name and services you probably don't need.
GPUBrazil offers the same NVIDIA GPUs (H100, A100, L40) at 50-77% lower prices with no hidden fees, no long-term commitments, and instant deployment.
The math is simple: at 77% savings, you could run 4x more experiments with the same budget, or pocket the savings and invest in your team.
Try GPUBrazil free today and see the difference yourself.