Quick Answer
io.net does not offer spot instances - all GPUs are on-demand with no interruptions. Unlike AWS spot instances that can be terminated with 2-minute notice, every io.net GPU is guaranteed for the duration of your job. Despite being fully on-demand, io.net's pricing ($0.18-$2.20/hr) is already 50-70% cheaper than AWS/Azure spot pricing, eliminating the need for interruptible instances. This means you get spot-like savings with on-demand reliability, making io.net ideal for both production workloads and cost-sensitive projects without the complexity of spot instance management or unexpected terminations.
Why io.net Doesn't Need Spot Instances
Traditional cloud providers use spot instances to sell excess capacity at discounts. io.net's decentralized model makes this unnecessary:
Traditional Cloud Spot Economics:
- Build data centers with excess capacity for peak demand
- Sell unused capacity at 60-90% discounts (spot pricing)
- Terminate spot instances when on-demand customers need capacity
- Customers must handle interruptions and checkpointing
io.net Decentralized Economics:
- Aggregate idle GPUs from 200,000+ independent providers globally
- No excess capacity problem - providers set their own competitive market rates
- Lower baseline costs (no data center construction, minimal overhead)
- Base pricing is already 50-70% below traditional cloud on-demand rates
Result: io.net's on-demand prices are cheaper than AWS/Azure spot prices, with zero interruption risk.
Pricing Comparison: io.net On-Demand vs. AWS/Azure Spot
Real pricing for common GPU workloads:
| GPU Model | io.net On-Demand | AWS Spot (avg) | Azure Spot (avg) | io.net Savings vs Spot |
|---|---|---|---|---|
| RTX 4090 | $0.18/hr | N/A | N/A | N/A |
| A100 40GB | $1.20/hr | $1.53/hr | $1.68/hr | 22-29% cheaper |
| A100 80GB | $1.49/hr | $2.05/hr | $2.31/hr | 27-35% cheaper |
| H100 SXM | $2.20/hr | $3.49/hr | $3.92/hr | 37-44% cheaper |
| H100 PCIe | $1.49/hr | $2.49/hr | $2.78/hr | 40-46% cheaper |
AWS spot pricing reflects typical availability (varies by region and time). Azure spot pricing reflects observed averages over 30 days in April 2026.
Key Insight: io.net's guaranteed on-demand H100 at $2.20/hr costs less than AWS spot H100 at $3.49/hr, which can be terminated anytime. You get better pricing AND better reliability.
The Hidden Costs of Spot Instances
While spot instance hourly rates look attractive, total cost of ownership is higher:
1. Interruption Overhead:
- AWS spot instances are terminated when capacity is needed (typically 10-30% interruption rate for GPUs)
- Each interruption wastes partial work since last checkpoint
- For a 24-hour training job with 3 interruptions, you might waste 2-4 hours of compute
Example:
- AWS spot A100: $1.53/hr × 24 hours = $36.72
- 3 interruptions with 1 hour wasted each = $1.53 × 3 = $4.59 additional cost
- Total: $41.31
- io.net A100: $1.20/hr × 24 hours = $28.80 (30% cheaper, zero interruptions)
2. Checkpointing Infrastructure:
To handle spot interruptions, you must:
- Implement checkpoint logic in training code
- Store checkpoints in persistent storage ($0.08-$0.12/GB/month on AWS)
- Monitor spot termination notices (2-minute warning)
- Automate instance replacement and checkpoint restoration
This engineering overhead costs 10-20 hours of developer time ($1,500-$3,000 at $150/hr).
3. Spot Price Volatility:
Spot prices fluctuate based on demand:
- During peak hours (9am-5pm US time), spot prices can spike 2-3x
- During regional outages, spot availability drops to zero
- Price spikes can make jobs 50-100% more expensive than expected
io.net pricing is stable and transparent - no surprise price increases.
Spot Instance Interruption Rates by Provider
Real-world interruption frequency for GPU spot instances:
| Provider | GPU Type | Avg Interruption Rate | Max Observed Downtime |
|---|---|---|---|
| AWS | A100 (p4d spot) | 15-25% of instances/month | 8 hours (capacity shortage) |
| AWS | H100 (p5 spot) | 25-40% of instances/month | 24 hours (regional outage) |
| Azure | A100 (ND-series spot) | 10-20% of instances/month | 6 hours (maintenance) |
| GCP | A100 (preemptible) | 20-30% of instances/month | 12 hours (zone failure) |
| io.net | All GPUs | 0% (no spot model) | 0 hours planned terminations |
Interruption Impact:
For a 72-hour distributed training job across 8 GPUs:
- AWS spot: 15% chance of losing at least 1 GPU during job = 15% of jobs require restart
- io.net: 0% interruption rate = 100% job completion without restarts
When Teams Traditionally Used Spot Instances
Understanding spot instance use cases helps explain why io.net is better:
Use Case 1: Cost-Sensitive AI Training
- Old approach: Use AWS spot to save 60-70% vs. on-demand
- Problem: 20-30% of jobs interrupted, requiring restarts
- io.net solution: Same 60-70% savings vs. AWS on-demand, zero interruptions
Use Case 2: Batch Inference Jobs
- Old approach: Run overnight batch inference on spot instances
- Problem: Jobs fail 10-15% of nights, requiring manual restart
- io.net solution: Guaranteed completion, lower cost than spot
Use Case 3: Development and Testing
- Old approach: Use spot for non-critical dev work
- Problem: Interruptions disrupt developer flow
- io.net solution: Same low cost, no interruptions = higher productivity
Use Case 4: Fault-Tolerant Distributed Training
- Old approach: Use spot with robust checkpointing and auto-restart
- Problem: Engineering complexity, 15-25% overhead from interruptions
- io.net solution: No engineering overhead, lower total cost
io.net's Alternative: Reserved Capacity for Additional Savings
While io.net doesn't offer spot instances, enterprise customers can access reserved capacity for additional discounts:
Reserved Capacity Tiers:
| Commitment | Discount on Base Pricing | Availability Guarantee | Minimum Spend |
|---|---|---|---|
| None (On-Demand) | 0% (base: 50-70% off AWS) | 99%+ availability | No minimum |
| 3-Month Reserved | 10% additional discount | 99.5% SLA | $5,000/month |
| 6-Month Reserved | 15% additional discount | 99.5% SLA | $10,000/month |
| 12-Month Reserved | 20% additional discount | 99.9% SLA | $25,000/month |
Example Savings:
- io.net on-demand H100: $2.20/hr
- 12-month reserved: $1.76/hr (20% additional discount = 75% cheaper than AWS on-demand)
- AWS spot H100: $3.49/hr (still 49% more expensive than io.net reserved)
No penalties for early termination - unlike AWS reserved instances that lock you into 1-3 year contracts.
How to Maximize Savings Without Spot Risk
Strategies to achieve spot-like economics on io.net:
1. Right-Size Your GPU Selection:
Don't overpay for performance you don't need:
- Inference workloads: Use RTX 4090 ($0.18/hr) instead of A100 ($1.20/hr) - same throughput, 85% savings
- Fine-tuning small models: Use A100 40GB ($1.20/hr) instead of A100 80GB ($1.49/hr) - 19% savings
- Batch processing: Scale horizontally with cheaper GPUs vs. vertically with expensive ones
2. Optimize Utilization:
Pay only for active compute time:
- Stop instances when not in use (per-second billing means no waste)
- Use auto-scaling for inference workloads (scale down during low traffic)
- Batch multiple experiments into single GPU sessions
3. Schedule Long-Running Jobs:
For multi-day training:
- Enable checkpointing (even though interruptions don't happen, checkpoints protect against code bugs)
- Monitor GPU utilization - if utilization drops below 80%, investigate efficiency issues
4. Use Multi-GPU Clusters Efficiently:
Distributed training should maintain >85% GPU utilization:
# Monitor cluster efficiency
io stats --cluster-id <cluster-id> --metric utilization
# Auto-scale cluster based on workload
io autoscale --cluster-id <cluster-id> --min-gpus 2 --max-gpus 16
Spot Instance Myths Debunked
Common misconceptions about cloud GPU pricing:
Myth 1: "Spot instances are always the cheapest option"
- Reality: io.net on-demand is 22-46% cheaper than AWS/Azure spot with zero interruption risk.
Myth 2: "You need spot instances for batch workloads to be cost-effective"
- Reality: io.net's per-second billing and low base pricing make on-demand instances perfect for batch jobs. No interruption complexity, lower total cost.
Myth 3: "Spot instance interruptions aren't a big deal with checkpointing"
- Reality: Each interruption wastes 15-30 minutes of compute (checkpoint save time + restore time + instance replacement). Over dozens of experiments, this adds 10-20% overhead.
Myth 4: "Decentralized GPUs are less reliable than spot instances"
- Reality: io.net maintains 99%+ uptime vs. spot instances with 10-30% interruption rates. Decentralization creates redundancy, not fragility.
Myth 5: "On-demand pricing is too expensive for AI training"
- Reality: io.net's on-demand pricing is 50-70% cheaper than AWS on-demand, making it affordable for most training workloads without spot complexity.
Production Reliability Without Spot Complexity
Why io.net's model is better for production AI workloads:
Spot Instance Production Challenges:
- Inference APIs fail when spot instances terminate (bad user experience)
- Training jobs require complex orchestration (Kubernetes with spot handling, custom checkpointing)
- Cost unpredictability (spot price spikes during peak demand)
- DevOps overhead (monitoring spot termination notices, automating replacements)
io.net Production Benefits:
- Inference APIs never fail due to instance termination
- Training jobs run to completion without interruption logic
- Predictable costs (stable pricing, no spikes)
- Zero DevOps overhead for instance lifecycle management
Real-World Example:
AI startup running LLM inference API:
- AWS spot approach: 3 interruptions/week requiring manual intervention, 15% downtime, $2,400/month
- io.net approach: Zero downtime, no manual intervention, $1,800/month (25% cheaper, 100% more reliable)
Cost Analysis: 30-Day Training Workload
Real TCO comparison for a typical AI research project:
Scenario: Train Llama 3 70B model on 8x A100 80GB for 120 hours over 30 days (multiple experiments)
AWS Spot (p4d.24xlarge):
- Spot price: $2.05/hr per A100 × 8 GPUs = $16.40/hr
- Total hours: 120 hours
- Base cost: $1,968
- Interruptions: ~3 interruptions × 2 hours wasted = 6 hours additional
- Checkpoint storage: 500GB × $0.10/GB/month = $50
- Data egress: 1TB × $0.09/GB = $90
- Total cost: $2,206
io.net (on-demand):
- On-demand price: $1.49/hr per A100 × 8 GPUs = $11.92/hr
- Total hours: 120 hours
- Base cost: $1,430
- Interruptions: 0 hours wasted
- Checkpoint storage: 500GB × $0.05/GB/month = $25
- Data egress: First 1TB free = $0
- Total cost: $1,455
Savings: $751 (34% cheaper) with zero interruptions and zero engineering overhead
Related Questions
Can I use io.net for fault-tolerant workloads that would typically use spot instances?
Yes, and you'll save money compared to spot instances. io.net's on-demand pricing is 22-46% cheaper than AWS/Azure spot while providing guaranteed availability. For workloads designed to handle spot interruptions (e.g., distributed training with robust checkpointing), io.net delivers the same or better cost efficiency without the interruption complexity. You can remove spot handling code and still save 30-50% vs. traditional cloud spot instances.
What happens if io.net runs out of capacity?
io.net has 200,000+ GPUs across 130+ countries, making capacity shortages extremely rare. If your preferred GPU type is temporarily unavailable (e.g., H100 in US-West at 3pm on Tuesday), you can either select a different region (EU-West, US-East) or set up an availability alert to provision when capacity returns. Unlike spot instances that terminate your running jobs when capacity is needed, io.net never terminates running instances - once you provision a GPU, it's yours until you stop it.
How does io.net pricing stay stable without spot/on-demand pricing tiers?
io.net uses a decentralized marketplace where independent GPU providers set competitive rates. Since providers want consistent utilization, they price to maintain steady demand rather than creating artificial scarcity. The platform aggregates global supply, smoothing out regional demand spikes that cause spot price volatility on traditional clouds. Additionally, io.net's lower overhead (no data center construction, minimal sales teams) allows for stable low pricing without needing dynamic pricing models.
Is io.net suitable for production inference workloads?
Absolutely. io.net's guaranteed availability makes it ideal for production inference APIs, unlike spot instances that can terminate mid-request. Many companies run production inference on io.net at 60-70% lower cost than AWS on-demand with higher reliability than spot instances. Use load balancing across 2-3 GPUs for 99.9%+ availability, or enterprise SLA plans for mission-critical workloads. RTX 4090 at $0.18/hr delivers excellent inference performance at a fraction of AWS Inferentia or Spot instance costs.
Can I pre-empt my own jobs to save money?
While io.net doesn't offer spot instances with pre-emption, you can achieve similar cost efficiency through: (1) Per-second billing - stop instances immediately when jobs complete to avoid paying for idle time, (2) Auto-scaling - scale down GPU clusters during low-demand periods, (3) Reserved capacity - commit to 3-12 month usage for 10-20% additional discounts. These approaches provide spot-like economics without the complexity of pre-emption handling.
Get Spot-Like Savings Without Interruption Risk
Experience the best of both worlds:
- Up to 70% cheaper than AWS on-demand - same savings as spot instances
- Zero interruptions - guaranteed availability, no spot terminations
- Stable pricing - no spot price volatility or surprise spikes
- No engineering overhead - eliminate spot handling code and checkpointing complexity
Compare pricing → or start deploying now →
Last updated: April 2026 | Spot pricing comparisons based on AWS/Azure observed averages over 30-day period
