Cloudzy vs Wafer: Pricing, Specs, Strengths & Weaknesses

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

Overview

Attribute

Cloudzy

Wafer

Provider type

Specialist

Founded

2008

2023

Headquarters

Dubai, UAE

United States

Billing model

Monthly, Annual (35% off)

On-demand

Min commitment

1 month

None

Support tier

Standard (24/7 human support)

Standard

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

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Wafer

Wafer offers H100 and A100 GPU cloud compute for AI and ML teams with straightforward on-demand pricing and flexible instance options that make it easy to scale training and inference workloads without complex billing structures. Simple setup and transparent pricing lower the barrier to entry for startups and small teams exploring GPU compute for LLM fine-tuning and model deployment. A no-frills on-demand GPU cloud for AI teams that want clear pricing and flexible instance configurations.

Strengths