Table of Contents
The Crisis
In 2025, the AI industry faces its biggest bottleneck: not algorithms, not data, but raw computing power. The explosive growth of AI applications — from ChatGPT to autonomous vehicles — has created demand that far exceeds the world's GPU supply.
NVIDIA's H100 GPU, the workhorse of AI training, has become the most sought-after chip in history. Wait times stretch to 6-12 months. Prices on secondary markets hit 2-3x MSRP. Even trillion-dollar companies struggle to secure enough capacity.
The Scale of the Problem
NVIDIA shipped ~2 million H100s in 2025, but demand exceeded 5 million units. This 3x gap means most companies simply cannot access the compute they need, regardless of budget. The shortage is expected to persist through 2026.
Root Causes
The GPU shortage isn't caused by a single factor, but a perfect storm of demand explosion and supply constraints:
Explosive AI Demand
ChatGPT, Midjourney, and enterprise AI adoption created unprecedented demand. AI compute needs doubled in 2024.
Manufacturing Bottlenecks
TSMC produces 90%+ of advanced chips. Building new fabs takes 3-5 years and $20B+ investment.
Hyperscaler Hoarding
Microsoft, Google, Meta bought H100s in bulk. Smaller companies struggle to access any capacity.
Geopolitical Tensions
US-China chip restrictions disrupted supply chains. Export controls limit where GPUs can be sold.
Power & Cooling Limits
Data centers hit power caps. A single H100 cluster needs megawatts of electricity.
Long Lead Times
H100 orders have 6-12 month wait times. Companies plan GPU purchases years in advance.
Industry Impact
The shortage affects different sectors in different ways:
| Sector | Impact | Key Stat |
|---|---|---|
AI Startups Many startups can't access GPUs at any price. Forced to delay products or pivot to CPU-only solutions. | Critical | 60% report GPU access issues |
Research Labs Academic research slowed. Labs share limited GPU time, extending experiment cycles from days to months. | Severe | 3-6 month wait times |
Enterprises Fortune 500 companies pay premium prices or delay AI initiatives. Some build private data centers. | High | 2-3x price premium |
Cloud Providers AWS, GCP, Azure have GPUs but at high prices. Spot instances unavailable for weeks. | Moderate | $3-4/hr for H100 |
By the Numbers
The Hidden Opportunity
While datacenter GPUs are scarce, there are 500+ million consumer GPUs sitting idle in gaming PCs worldwide. These represent an untapped reservoir of compute power — the foundation of DePIN solutions.
Available Solutions
Companies facing the GPU shortage have several options, each with trade-offs:
Centralized Cloud
AWS, GCP, Azure
- Reliable
- Enterprise support
- Global availability
- Expensive ($3-4/hr H100)
- Capacity limits
- Vendor lock-in
GPU Cloud Startups
Lambda, CoreWeave
- Lower prices
- GPU-focused
- Better availability
- Limited regions
- Smaller scale
- Less enterprise features
DePIN Networks
Griddly, Render, Akash
- 70% cheaper
- Distributed supply
- No capacity limits
- Newer technology
- Variable performance
- Different workflow
On-Premise
Self-hosted
- Full control
- No ongoing costs
- Data privacy
- $30K+ per H100
- Long wait times
- Maintenance burden
The DePIN Revolution
Decentralized Physical Infrastructure Networks (DePIN) are emerging as a powerful solution to the compute shortage. By aggregating idle GPUs from millions of individual contributors, DePIN networks create a distributed supercomputer.
Why DePIN Works
Future Outlook
The GPU shortage will persist through 2026, but the landscape is evolving:
2025-2026: Peak Shortage
Demand continues to outpace supply. H100 remains scarce. B100/B200 (Blackwell) launches but faces similar constraints. DePIN adoption accelerates as traditional options remain expensive.
2027-2028: Relief Begins
New fabs come online (TSMC Arizona, Intel). Supply catches up to current demand, but AI adoption continues growing. Hybrid cloud + DePIN becomes standard architecture for AI companies.
2029+: New Equilibrium
Market matures. Multiple GPU vendors (NVIDIA, AMD, Intel, custom chips). DePIN networks become mainstream infrastructure, handling 20-30% of global AI compute.
Griddly's Role
Griddly is building the infrastructure to solve the compute shortage from both sides:
For GPU Owners
- Earn $50-200/month from idle GPUs
- Simple one-click setup with Griddly Hub
- Automatic workload management
- Instant withdrawals via PayPal/crypto
For AI Companies
- A100s from $0.80/hr, H100s from $1.99/hr
- 70% cheaper than AWS/GCP
- No waitlists or capacity limits
- API-compatible with existing workflows