Provider Overview
Strengths & Best For
Salad leverages a distributed network of consumer GPUs — including RTX 4090 and RTX 3090 — to deliver some of the lowest AI inference prices on the market, making it ideal for batch image generation, LLM inference, and cost-sensitive AI workloads. The marketplace model enables per-use billing with no minimum commitment, dramatically undercutting traditional on-demand GPU cloud pricing for fault-tolerant jobs. Best suited for workloads that can tolerate variable hardware rather than requiring guaranteed uptime.
- Extremely low prices
- Consumer GPU network
- Batch inference focus
- Pay-per-use
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
Salad — marketplace provider
Salad leverages a distributed network of consumer GPUs — including RTX 4090 and RTX 3090 — to deliver some of the lowest AI inference prices on the market, making it ideal for batch image generation, LLM inference, and cost-sensitive AI workloads. The marketplace model enables per-use billing with no minimum commitment, dramatically undercutting traditional on-demand GPU cloud pricing for fault-tolerant jobs. Best suited for workloads that can tolerate variable hardware rather than requiring guaranteed uptime.
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
Salad uses a Per-use (serverless) 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
Salad is best suited for: Budget inference workloads, Image generation pipelines, Cost-sensitive batch jobs. Its key strengths are extremely low prices, consumer gpu network, batch inference focus. 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
Salad offers Community → Pro support across 2 regions (US, EU). IO.NET offers Community support across 1 region (Various). Salad's broader region footprint gives it an advantage for latency-sensitive workloads or teams with data residency requirements in specific geographies.
Provider background: Salad vs IO.NET
Salad was founded in 2020 and is headquartered in Boston, MA. IO.NET was founded in 2023 and is headquartered in San Francisco, CA. Salad has 3 years more operational history than IO.NET, which may matter for teams evaluating provider stability and long-term contract risk. 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.