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Compare GPU and LLM inference API pricing between Groq and IO.NET. Find the best rates for AI training, inference, and ML workloads.
Provider 1
Provider 2
| GPU Model ↑ | Groq Price | IO.NET Price | Price Diff ↕ | Sources |
|---|---|---|---|---|
A100 PCIE 40GB VRAM • IO.NET | Not Available | — | ||
A100 PCIE 40GB VRAM • | ||||
A100 SXM 80GB VRAM • IO.NET | Not Available | 2x GPU | — | |
A100 SXM 80GB VRAM • | ||||
A30 24GB VRAM • IO.NET | Not Available | 4x GPU | — | |
A30 24GB VRAM • | ||||
A40 48GB VRAM • IO.NET | Not Available | — | ||
A40 48GB VRAM • | ||||
Gaudi 2 96GB VRAM • IO.NET | Not Available | 8x GPU | — | |
Gaudi 2 96GB VRAM • | ||||
H100 SXM 80GB VRAM • IO.NET | Not Available | 4x GPU | — | |
H100 SXM 80GB VRAM • | ||||
H200 141GB VRAM • IO.NET | Not Available | — | ||
H200 141GB VRAM • | ||||
L4 24GB VRAM • IO.NET | Not Available | 8x GPU | — | |
L4 24GB VRAM • | ||||
L40 40GB VRAM • IO.NET | Not Available | — | ||
L40 40GB VRAM • | ||||
L40S 48GB VRAM • IO.NET | Not Available | 4x GPU | — | |
L40S 48GB VRAM • | ||||
RTX 4000 Ada 20GB VRAM • IO.NET | Not Available | — | ||
RTX 4000 Ada 20GB VRAM • | ||||
RTX 6000 Ada 48GB VRAM • IO.NET | Not Available | — | ||
RTX 6000 Ada 48GB VRAM • | ||||
RTX A6000 48GB VRAM • IO.NET | Not Available | — | ||
RTX A6000 48GB VRAM • | ||||
RTX PRO 6000 96GB VRAM • IO.NET | Not Available | 4x GPU | — | |
RTX PRO 6000 96GB VRAM • | ||||
Tesla T4 16GB VRAM • IO.NET | Not Available | — | ||
Tesla T4 16GB VRAM • | ||||
A100 PCIE 40GB VRAM • IO.NET | Not Available | — | ||
A100 PCIE 40GB VRAM • | ||||
A100 SXM 80GB VRAM • IO.NET | Not Available | 2x GPU | — | |
A100 SXM 80GB VRAM • | ||||
A30 24GB VRAM • IO.NET | Not Available | 4x GPU | — | |
A30 24GB VRAM • | ||||
A40 48GB VRAM • IO.NET | Not Available | — | ||
A40 48GB VRAM • | ||||
Gaudi 2 96GB VRAM • IO.NET | Not Available | 8x GPU | — | |
Gaudi 2 96GB VRAM • | ||||
H100 SXM 80GB VRAM • IO.NET | Not Available | 4x GPU | — | |
H100 SXM 80GB VRAM • | ||||
H200 141GB VRAM • IO.NET | Not Available | — | ||
H200 141GB VRAM • | ||||
L4 24GB VRAM • IO.NET | Not Available | 8x GPU | — | |
L4 24GB VRAM • | ||||
L40 40GB VRAM • IO.NET | Not Available | — | ||
L40 40GB VRAM • | ||||
L40S 48GB VRAM • IO.NET | Not Available | 4x GPU | — | |
L40S 48GB VRAM • | ||||
RTX 4000 Ada 20GB VRAM • IO.NET | Not Available | — | ||
RTX 4000 Ada 20GB VRAM • | ||||
RTX 6000 Ada 48GB VRAM • IO.NET | Not Available | — | ||
RTX 6000 Ada 48GB VRAM • | ||||
RTX A6000 48GB VRAM • IO.NET | Not Available | — | ||
RTX A6000 48GB VRAM • | ||||
RTX PRO 6000 96GB VRAM • IO.NET | Not Available | 4x GPU | — | |
RTX PRO 6000 96GB VRAM • | ||||
Tesla T4 16GB VRAM • IO.NET | Not Available | — | ||
Tesla T4 16GB VRAM • | ||||
| Model ↑ | Groq | IO.NET | Input Diff ↕ |
|---|---|---|---|
DeepSeek | Not available | $0.568 in $2.28 out | — |
DeepSeek | Not available | $1.49 in $2.66 out | — |
DeepSeek | Not available | $0.199 in $0.512 out | — |
DeepSeek | Not available | $1.75 in $3.49 out | — |
Google | Not available | $0.122 in $0.420 out | — |
Zhipu | Not available | $0.063 in $0.400 out | — |
Zhipu | Not available | $0.157 in $0.937 out | — |
Zhipu | Not available | $0.536 in $2.07 out | — |
Zhipu | Not available | $0.880 in $2.37 out | — |
Zhipu | Not available | $0.860 in $2.78 out | — |
Zhipu | Not available | $1.33 in $4.22 out | — |
Zhipu | Not available | $1.82 in $5.72 out | — |
Z AI | Not available | $1.32 in $4.31 out | — |
Z AI | Not available | $0.150 in $0.500 out | — |
OpenAI | $0.150 in $0.600 out | $0.178 in $0.680 out | $0.028 |
Explore how these providers compare to other popular GPU cloud services
Compare Groq with another leading provider
Compare Groq with another leading provider
Compare Groq with another leading provider
Compare Groq with another leading provider
Compare Groq with another leading provider
Compare Groq with another leading provider
Custom Language Processing Units run inference, with 256 LPUs and 128 GB of on-chip SRAM per rack
Drop-in replacement for the OpenAI API at api.groq.com/openai/v1, including a Responses API
GroqMetal bare-metal infrastructure, GroqCore inference stack, and GroqAssured enterprise governance, each including the layers below
Text generation plus speech-to-text, text-to-speech, OCR and image recognition, and content moderation models
Compound systems that combine models with web search, code execution, remote MCP tools, and Google Workspace connectors
Performance, flex, and batch processing tiers, plus prompt caching, structured outputs, and LoRA inference
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.
Token-based pricing with separate input/output rates; audio models are billed per hour and speech models per character
Alternative service tiers for throughput-tolerant or bursty workloads instead of the standard on-demand tier
Dedicated capacity and enterprise-only models quoted through sales
Rate-limited free access for development and testing
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
Sign up at console.groq.com with email or OAuth
Generate an API key from the console dashboard
Use the OpenAI-compatible endpoint with your preferred model
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
13 data centers across four continents, including sites in the US (Liberty Lake, St Paul, Dallas, Houston), Canada (Kamloops, Vaudreuil-Dorion, Calgary), Finland, the UK, Australia, and Saudi Arabia
Documentation and API reference, developer community, production readiness guides, and enterprise onboarding via sales
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