Provider Overview
Strengths & Best For
Corelink is a GPU cloud offering H100, H200, A100, and L40S instances with flexible billing, spot availability, and competitive on-demand pricing for AI training and inference workloads. The self-serve platform makes it easy to provision GPU capacity for LLM fine-tuning, distributed training, and model deployment without enterprise contracts. A straightforward on-demand GPU cloud for startups and research teams that need H100 access at competitive rates.
- Competitive H100 pricing
- Spot availability
- Flexible billing
- Wide GPU selection
IO.NET is a decentralized GPU network aggregating idle compute from data centers, crypto miners, and consumer hardware — including H100 and A100 — at prices typically well below traditional on-demand GPU cloud providers. The marketplace model enables batch AI inference, LLM training, and distributed workloads at dramatically reduced cost for teams comfortable with variable hardware reliability. A compelling option for crypto-native teams and cost-sensitive developers who can tolerate the trade-offs of a decentralized GPU network.
- Very low prices on H100 and A100
- Large pool of available GPUs
- Decentralized resilience
- Crypto-native billing
Live GPU Pricing
Region Coverage
Popular Comparisons
Corelink — specialist provider
Corelink is a GPU cloud offering H100, H200, A100, and L40S instances with flexible billing, spot availability, and competitive on-demand pricing for AI training and inference workloads. The self-serve platform makes it easy to provision GPU capacity for LLM fine-tuning, distributed training, and model deployment without enterprise contracts. A straightforward on-demand GPU cloud for startups and research teams that need H100 access at competitive rates.
IO.NET — marketplace provider
IO.NET is a decentralized GPU network aggregating idle compute from data centers, crypto miners, and consumer hardware — including H100 and A100 — at prices typically well below traditional on-demand GPU cloud providers. The marketplace model enables batch AI inference, LLM training, and distributed workloads at dramatically reduced cost for teams comfortable with variable hardware reliability. A compelling option for crypto-native teams and cost-sensitive developers who can tolerate the trade-offs of a decentralized GPU network.
Billing model comparison
Corelink uses a On-demand, Spot billing model with a minimum commitment of None. IO.NET uses On-demand billing with a None minimum. Both providers offer flexible billing options — compare the live pricing table above to find the best rate for your specific GPU model and workload duration.
Which workloads each provider suits best
Corelink is best suited for: Cost-sensitive AI training, Spot-tolerant workloads, Startups needing H100 access. Its key strengths are competitive h100 pricing, spot availability, flexible billing. IO.NET is best suited for: Batch inference, Cost-sensitive training, Crypto-native teams. Its key strengths are very low prices on h100 and a100, large pool of available gpus, decentralized resilience. Marketplace providers aggregate GPU supply from multiple sources, often offering the lowest spot rates but with more variable availability and less predictable performance compared to dedicated providers.
Support tiers and region coverage
Corelink offers Community → Standard support across 1 region (US). IO.NET offers Community support across 1 region (Various). Both providers have comparable region coverage — choose based on which specific regions overlap with your user base or data residency requirements.
Provider background: Corelink vs IO.NET
Corelink was founded in 2023 and is headquartered in United States. IO.NET was founded in 2023 and is headquartered in San Francisco, CA. Both providers were founded in the same year — evaluate them on current pricing, region coverage, and support tier rather than operational history. Use the live pricing table above to compare current on-demand and spot rates for specific GPU models, and the region map to verify coverage in your target geography.