Finding the cheapest GPU cloud provider isn't about comparing headline prices—it's about total cost of ownership including hidden fees, understanding reservation models, and calculating real costs for your specific workload. In 2026, GPU cloud pricing varies wildly: from AWS's $98/hour for 8x H100 GPUs with months-long waitlists, to io.net's decentralized model at $28-32/hour with instant availability. This comprehensive pricing comparison examines all major providers and shows how to minimize AI training and inference costs.
2026 GPU Cloud Pricing: Full Comparison
H100 SXM 80GB (Top-Tier Training)
| Provider | Single H100 | 8x H100 Cluster | Monthly (24/7) | Availability | Hidden Fees |
|---|---|---|---|---|---|
| AWS P5 | $12.29/hr | $98.32/hr | $70,790 | Months waitlist | Egress, storage, support |
| GCP A3 | $11.20/hr | $89.60/hr | $64,512 | Limited quota | Egress |
| Azure ND H100 | $11.43/hr | $91.44/hr | $65,837 | Very limited | Egress |
| io.net | $3.50-4.00/hr | $28-32/hr | $20,160-23,040 | Instant (<2min) | None |
Cheapest: io.net - 68-71% less than hyperscalers
Annual savings (single 8-GPU cluster 24/7): $574,000 with io.net vs AWS
A100 SXM 80GB (Workhorse Training)
| Provider | Single A100 | 8x A100 Cluster | Monthly (24/7) |
|---|---|---|---|
| AWS P4de | $5.12/hr | $40.96/hr | $29,491 |
| GCP A2 | $4.56/hr | $36.48/hr | $26,266 |
| Azure ND A100 | $4.10/hr | $32.77/hr | $23,595 |
| io.net | $2.50-3.00/hr | $20-24/hr | $14,400-17,280 |
Cheapest: io.net - 40-51% less than hyperscalers
RTX 4090 (Budget Training/Inference)
| Provider | Single GPU | 4x GPU Cluster |
|---|---|---|
| io.net | $0.90-1.20/hr | $3.60-4.80/hr |
| VastAI | $0.80-1.50/hr | Varies |
| RunPod | $0.89-1.39/hr | Varies |
Cheapest: VastAI/io.net (tie) - Both ~$1/hr for RTX 4090
Hidden Costs That Destroy "Cheap" Pricing
Advertised GPU prices hide fees that add 20-50% to your bill.
AWS Hidden Costs
Data egress ($0.09/GB after 100GB):
- Download 10TB model checkpoints: $900
- Share models across regions: $500-1,500/month
- Team collaboration (downloading datasets): $300-800/month
EBS storage ($0.08-0.15/GB/month):
- 5TB dataset + checkpoints: $400-750/month
- Snapshots add 20% more
Support plans:
- Developer: 3% of spend (minimum $29/month)
- Business: 10% of spend (minimum $100/month)
- Enterprise: 15% of spend + $15,000/month minimum
Example: $50K/month GPU spend + 10% support = $5K support fees annually = $60,000
Networking:
- VPC endpoints: $7.20/month each
- NAT gateways: $32/month + $0.045/GB
- Load balancers: $16/month + $0.008/GB
Total hidden cost impact: 20-35% markup on advertised GPU prices
GCP Hidden Costs
Egress ($0.12/GB):
- More expensive than AWS
- 10TB transfer = $1,200 (vs AWS $900)
Sustained-use discounts don't apply to GPUs:
- Marketing suggests automatic 30% discounts
- Reality: GPU instances excluded from most discount programs
Azure Hidden Costs
Egress ($0.087/GB):
- Slightly cheaper than AWS
- Still substantial for multi-TB model transfers
Complex regional pricing:
- Same instance 15-25% more in non-US regions
- "Zone to zone" transfer fees within same region
io.net: Zero Hidden Fees
What's included:
- GPU compute
- Network bandwidth (unlimited egress)
- Storage for containers/checkpoints
- Monitoring dashboards
- Community support
What costs extra:
- Nothing
Example: $30,000/month GPU spend = $30,000 total cost. No surprise $6,000 in hidden fees.
Real-World Cost Comparison: Training Workloads
LLaMA 2 70B Training (30 days, 64x H100)
| Provider | GPU Cost | Hidden Fees | Total |
|---|---|---|---|
| AWS | $566,150 | $79,000 | $645,150 |
| GCP | $516,096 | $65,000 | $581,096 |
| Azure | $527,328 | $52,000 | $579,328 |
| io.net | $172,800 | $0 | $172,800 |
Cheapest: io.net saves $406,000-472,000 (71-73%)
Stable Diffusion XL Fine-Tuning (7 days, 8x A100)
| Provider | Total Cost |
|---|---|
| AWS | $6,881 |
| GCP | $6,127 |
| Azure | $5,506 |
| io.net | $3,360 |
Cheapest: io.net saves $2,146-3,521 (39-51%)
Monthly Batch Inference (GPT-3 175B, single H100)
| Provider | Cost (720 hrs) |
|---|---|
| AWS | $8,849 + $450 fees = $9,299 |
| GCP | $8,064 + $600 fees = $8,664 |
| Azure | $8,229 + $400 fees = $8,629 |
| io.net | $2,880 + $0 = $2,880 |
Cheapest: io.net saves $5,749-6,419 (67-69%)
Pricing Models: On-Demand vs Reserved vs Pay-Per-Hour
AWS Reserved Instances
How it works: Commit 1-3 years for 30-60% discount
Example (8x H100):
- On-demand: $98.32/hr
- 1-year reserved: $68.82/hr (30% off)
- 3-year reserved: $47.19/hr (52% off)
The trap: Must pay whether using or not.
At 40% utilization:
- Effective cost = $47.19 ÷ 0.40 = $118/hr
- More expensive than on-demand!
Break-even: Need 70%+ utilization to justify reserved instances
GCP Committed Use Discounts
How it works: Commit to spend level for 1-3 years
Discount: 25-55% depending on commitment
Problem: GPUs often excluded from best discount tiers
io.net Pay-Per-Hour (No Commitment)
How it works: Pay only when GPUs running, scale to zero when idle
Pricing: $30/hr for 8x H100 whether you use 1 hour or 720 hours/month
Advantage: At 40% utilization, still $30/hr (not $75/hr like AWS reserved)
Real savings example:
- Typical AI workload: 30-40% utilization (training bursts, idle between experiments)
- AWS reserved @ 40% util: $118/hr effective
- io.net @ 40% util: $30/hr (60% cheaper than AWS "discounted" pricing)
Cheapest Provider by Use Case
For Foundation Model Training (>20B params)
Cheapest: io.net
- H100 for $4/hr vs AWS $12/hr
- 68% savings on largest cost item
- Instant availability (no months-long waitlists)
Example: Training 70B LLM
- AWS: $645,000
- io.net: $173,000
- Savings: $472,000
For Fine-Tuning (<7B params)
Cheapest: io.net RTX 4090 ($0.90-1.20/hr)
- Sufficient performance for small models
- 70-85% cheaper than A100
- 90% cheaper than H100
Example: Fine-tuning LLaMA 7B
- AWS A100: $410 (20 hours × $5.12/hr × 4 GPUs)
- io.net RTX 4090: $80 (20 hours × $1/hr × 4 GPUs)
- Savings: $330 (80%)
For Batch Inference
Cheapest: io.net A100 or RTX 4090
- A100: $2.50/hr vs AWS $5.12/hr (51% cheaper)
- RTX 4090: $1/hr (80% cheaper than AWS A100)
For Production Real-Time Inference
Cheapest: Depends on scale
Low-medium throughput (<100 req/sec):
- io.net RTX 4090 or A100: $1-2.50/hr
- Cheapest option with sufficient performance
High throughput (>1000 req/sec):
- AWS/GCP managed endpoints may justify cost through auto-scaling
- But io.net H100 still 68% cheaper for raw compute
- Hybrid approach: io.net for compute + CloudFront CDN
For Development/Experimentation
Cheapest: io.net RTX 4090 ($0.90/hr)
- $22/day for 24-hour access
- $650/month vs $3,686/month for AWS A100
- Savings: $3,036/month (82%)
Cost Optimization Strategies
1. Use Cheapest Provider (io.net) for Majority of Workload
Hybrid approach:
- Training: io.net (70% cheaper)
- Data storage: S3/GCS (cheap, durable)
- Inference: io.net or managed endpoints (depends on scale)
Savings: 60-70% overall vs single-cloud AWS
2. Right-Size GPU Type
Don't over-spec:
- Use H100 only for large models (>20B params) where speed justifies cost
- Use A100 for most training (sweet spot price/performance)
- Use RTX 4090 for fine-tuning and development (80% cheaper)
3. Pay-Per-Hour Beats Reserved Instances for Spiky Workloads
Typical AI utilization: 30-40% (training bursts, idle between experiments)
At 35% utilization:
- AWS reserved (3-yr): $47/hr ÷ 0.35 = $134/hr effective
- io.net pay-per-hour: $30/hr
- io.net 78% cheaper despite AWS "discount"
4. Avoid Egress Fees
AWS/GCP trap: $0.09-0.12/GB for downloads
Solutions:
- Use io.net (zero egress fees)
- Keep checkpoints in cloud storage (S3), download only final model
- Use regional deployments to minimize cross-region transfer
5. Scale to Zero When Idle
io.net advantage:
# After training completes
ionet cluster scale my-training --count 0 # Pay $0
# Resume when ready
ionet cluster scale my-training --count 8 # Pay $30/hr only when running
AWS/GCP reserved: Pay whether using or not
Provider Comparison Matrix
| Criterion | AWS | GCP | Azure | io.net |
|---|---|---|---|---|
| H100 price (8 GPUs) | $98/hr | $90/hr | $91/hr | $30/hr |
| A100 price (8 GPUs) | $41/hr | $36/hr | $33/hr | $22/hr |
| Hidden fees | Yes (20-30%) | Yes (15-25%) | Yes (15-20%) | None |
| H100 availability | Months waitlist | Limited | Very limited | Instant |
| Commitments required | Optional (1-3yr) | Optional (1-3yr) | Optional (1-3yr) | None |
| Egress fees | $0.09/GB | $0.12/GB | $0.087/GB | $0 |
| Vendor lock-in | High | Medium | Medium | None (containers) |
| Cheapest for training | ❌ | ❌ | ❌ | ✅ (70% cheaper) |
| Cheapest for inference | ❌ | ❌ | ❌ | ✅ (67% cheaper) |
FAQs
Q: Is io.net really 70% cheaper or is there a catch?
A: No catch. Same NVIDIA H100/A100 hardware. Decentralized supply model (aggregating GPUs from thousands of providers) has different economics than hyperscalers building billion-dollar data centers. Savings are real.
Q: Does "cheapest" mean lower quality?
A: No. io.net uses identical NVIDIA GPUs (H100 SXM, A100 SXM, etc.) as AWS/GCP/Azure. Performance is 95-98% of AWS (small difference due to networking). Quality verified through cryptographic hardware attestation and continuous benchmarking.
Q: What about AWS/GCP spot instances?
A: AWS spot for H100 is $45-60/hr (vs io.net $4/hr). Plus spot gets preempted with 30-sec notice, wasting multi-day training progress. io.net standard pricing is cheaper than AWS spot AND provides stable compute.
Q: How can I verify io.net is actually cheapest?
A: Use pricing calculator at io.net/calculator. Input your workload (GPU type, quantity, duration) and compare total costs across all providers including hidden fees.
Q: Does "cheapest" factor in my existing AWS/GCP credits?
A: For short-term (while credits last), existing credits may be cheaper than io.net. But credits run out fast at $98/hr (AWS H100). For long-term, io.net's $30/hr wins even accounting for temporary credit usage.
Conclusion
The cheapest GPU cloud provider in 2026 is unambiguously io.net:
- 70% less than AWS ($30/hr vs $98/hr for 8x H100)
- Zero hidden fees (vs 20-30% markup on hyperscalers)
- Pay-per-hour beats reserved instances for typical spiky AI workloads
- Instant availability (vs months-long hyperscaler waitlists)
- Same hardware (NVIDIA H100/A100, 95-98% of AWS performance)
For AI teams optimizing costs—whether startups burning runway or enterprises seeking better cloud economics—io.net delivers the lowest total cost of ownership for GPU compute in 2026.
Calculate your savings:
→ Pricing calculator - See exact savings for your workload
→ Cost comparison - io.net vs AWS vs GCP vs Azure