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Compare GPU and LLM inference API pricing between IO.NET and Lambda Labs. Find the best rates for AI training, inference, and ML workloads.
Provider 1
Provider 2
| GPU Model ↑ | IO.NET Price | Lambda Labs Price | Price Diff ↕ | Sources |
|---|---|---|---|---|
A10 24GB VRAM • Lambda Labs | Not Available | — | ||
A10 24GB VRAM • | ||||
A100 SXM 80GB VRAM • Lambda Labs | Not Available | 4x GPU | — | |
A100 SXM 80GB VRAM • | ||||
B200 192GB VRAM • Lambda Labs | Not Available | 8x GPU | — | |
B200 192GB VRAM • | ||||
GH200 96GB VRAM • Lambda Labs | Not Available | — | ||
GH200 96GB VRAM • | ||||
H100 SXM 80GB VRAM • Lambda Labs | Not Available | 8x GPU | — | |
H100 SXM 80GB VRAM • | ||||
RTX A6000 48GB VRAM • Lambda Labs | Not Available | 2x GPU | — | |
RTX A6000 48GB VRAM • | ||||
Tesla V100 32GB VRAM • Lambda Labs | Not Available | 8x GPU | — | |
Tesla V100 32GB VRAM • | ||||
A10 24GB VRAM • Lambda Labs | Not Available | — | ||
A10 24GB VRAM • | ||||
A100 SXM 80GB VRAM • Lambda Labs | Not Available | 4x GPU | — | |
A100 SXM 80GB VRAM • | ||||
B200 192GB VRAM • Lambda Labs | Not Available | 8x GPU | — | |
B200 192GB VRAM • | ||||
GH200 96GB VRAM • Lambda Labs | Not Available | — | ||
GH200 96GB VRAM • | ||||
H100 SXM 80GB VRAM • Lambda Labs | Not Available | 8x GPU | — | |
H100 SXM 80GB VRAM • | ||||
RTX A6000 48GB VRAM • Lambda Labs | Not Available | 2x GPU | — | |
RTX A6000 48GB VRAM • | ||||
Tesla V100 32GB VRAM • Lambda Labs | Not Available | 8x GPU | — | |
Tesla V100 32GB VRAM • | ||||
Explore how these providers compare to other popular GPU cloud services
Compare IO.NET with another leading provider
Compare IO.NET with another leading provider
Compare IO.NET with another leading provider
Compare IO.NET with another leading provider
Compare IO.NET with another leading provider
Compare IO.NET with another leading provider
Access to 300,000+ verified GPUs from 139 countries with 6,000+ cluster-ready GPUs
Deploy clusters in under 90 seconds with auto-scaling capabilities
Choose from containers, Ray clusters, or bare metal based on workload needs
Uses the same distributed computing framework that OpenAI used to train GPT-3
AI models, smart agents, and API integration for workflow automation
Kernel-level VPN with secure mesh protocols for data protection
On-demand GPU clusters for AI/ML workloads with multiple deployment options
AI models, smart agents, and API integration platform
Decentralized pool of GPU providers with unified APIs and competitive pricing.
Most cost-effective option for distributed ML workloads using Ray framework
Standard containerized deployments with Docker support
Premium pricing for direct hardware access and maximum performance
Dynamic pricing based on actual resource usage with automatic scaling
Create an account on the IO.NET platform with no complex KYC requirements
Purchase $IO tokens for compute payments or add other supported payment methods
Select from containers, Ray clusters, or bare metal based on your workload
Specify GPU requirements, region preferences, and scaling options
Launch your cluster in under 90 seconds and start your AI/ML workloads
Global distributed network across 139 countries with intelligent geographic clustering and latency optimization
Documentation portal, Discord community (500,000+ members), Telegram support, and direct engineering support for GPU and driver questions