Cloudzy vs IO.NET: Pricing, Specs, Strengths & Weaknesses

Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for Cloudzy and IO.NET. Rates sourced from public APIs — verify current availability and billing terms before purchasing.

Overview

Attribute

Cloudzy

IO.NET

Provider type

Specialist

Marketplace

Founded

2008

2023

Headquarters

Dubai, UAE

San Francisco, CA

Billing model

Monthly, Annual (35% off)

On-demand

Min commitment

1 month

None

Support tier

Standard (24/7 human support)

Community

Regions

4 regions

1 regions

Strengths & Best For

Cloudzy

Cloudzy offers dedicated GPU VPS plans with RTX PRO 6000 Blackwell (96 GB GDDR7 ECC), Nvidia A100 (80 GB HBM2e), RTX 5090 (32 GB GDDR7), and RTX 4090 (24 GB GDDR6X) in 1× to 4× configurations. Annual pricing (35% off): RTX PRO 6000 $845/mo, A100 $714/mo, RTX 5090 $649/mo, RTX 4090 $506/mo. Monthly pricing: RTX PRO 6000 $1,300/mo, A100 $1,099/mo, RTX 5090 $999/mo, RTX 4090 $779/mo. All plans include CUDA pre-installed, AMD EPYC + DDR5, pure NVMe storage, 40 Gbps uplinks, and no egress fees. 14-day money-back guarantee. 13 global locations. Independent since 2008, rated 4.6/5 on Trustpilot. Accepts crypto (BTC, XMR, USDT).

Strengths

RTX PRO 6000 Blackwell (96 GB GDDR7 ECC) — dedicated passthrough
CUDA pre-installed — PyTorch, TF, JAX ready out of the box
40 Gbps uplinks, no egress fees, pure NVMe storage
35% annual discount — RTX PRO 6000 $845/mo, A100 $714/mo
14-day money-back guarantee
Accepts BTC, XMR, USDT crypto payments

Weaknesses

Monthly billing only — no per-hour or per-second options
No InfiniBand — multi-node training over standard Ethernet only
Smaller provider — limited scale vs hyperscalers

Best For

Teams wanting dedicated (non-shared) GPU VPSLLM inference on RTX PRO 6000 (96 GB VRAM)Long-running training jobs on dedicated hardwareCrypto-native teams

Visit Cloudzy

Cloudzy Rating

No reviews yet — add yours ↗

IO.NET

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.

Strengths