What is the difference between Groq and Wafer?

Groq and Wafer are both cloud GPU providers offering different pricing models, features, and GPU availability. Use our comparison tool to see real-time pricing and feature differences.

Which is cheaper: Groq or Wafer?

Pricing varies by GPU model and usage requirements. Check our real-time comparison table to find the best deals for your specific needs.

Can I switch between Groq and Wafer?

Yes, both providers offer flexible cloud GPU services. However, consider factors like data transfer costs, setup time, and specific features when switching between providers.

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Groq vs Wafer

Compare LLM inference API pricing between Groq and Wafer. Find the best rates for AI training, inference, and ML workloads.

Groq

Provider 1

Models Available

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Wafer

Provider 2

Models Available

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Comparison Overview

Total LLM Models

Groq Models

Wafer Models

Direct Comparisons

LLM API Pricing Comparison

Total models: 6Both available: 0Groq: 4Wafer: 2

Showing 6 of 6 models

Prices per 1M tokens · Last updated: 9/10/2026, 5:14:42 AM

Model ↑	Groq	Wafer	Input Diff ↕
GLM-5.1 Zhipu	Not available	$1.00 in $3.20 out	—
GLM-5.2 Zhipu	Not available	$1.20 in $4.10 out	—
GPT-OSS-120B OpenAI	$0.150 in $0.600 out	Not available	—
GPT-OSS-20B OpenAI	$0.075 in $0.300 out	Not available	—
Qwen 3.6 27B Alibaba	$0.600 in $3.00 out	Not available	—
Qwen3.8 27B Alibaba	$0.800 in $4.00 out	Not available	—

Features Comparison

Groq

LPU-Powered Inference
Custom Language Processing Units run inference, with 256 LPUs and 128 GB of on-chip SRAM per rack
OpenAI-Compatible API
Drop-in replacement for the OpenAI API at api.groq.com/openai/v1, including a Responses API
Layered Platform
GroqMetal bare-metal infrastructure, GroqCore inference stack, and GroqAssured enterprise governance, each including the layers below
Multimodal Endpoints
Text generation plus speech-to-text, text-to-speech, OCR and image recognition, and content moderation models
Agentic Systems and Built-In Tools
Compound systems that combine models with web search, code execution, remote MCP tools, and Google Workspace connectors
Service Tiers
Performance, flex, and batch processing tiers, plus prompt caching, structured outputs, and LoRA inference

Wafer

Serverless Inference
Pay-as-you-go API access to hosted open-source models including GLM, Kimi, Qwen, and DeepSeek with no infrastructure management
Dedicated Endpoints
Custom-tuned inference deployments with performance guarantees, provisioned in under 24 hours
Automated Performance Optimization
Agents profile inference bottlenecks and tune across serving engines (vLLM, SGLang, TensorRT-LLM), custom kernels (CUDA, HIP, Triton, NKI), quantization (FP8/FP4), and decode strategies
Multi-Accelerator Hardware
Workloads run on NVIDIA B200/B300, AMD MI350X/MI355X, and AWS Trainium depending on the model and traffic shape
OpenAI- and Anthropic-Compatible API
OpenAI-compatible endpoint at pass.wafer.ai/v1 and Anthropic-compatible endpoint at pass.wafer.ai/v1/messages, both using Bearer token authentication
Prompt Caching
Cached input tokens are billed at reduced rates on supported models

Pros & Cons

Groq

Advantages

High published token speeds (500 t/s on GPT-OSS 120B, 1,000 t/s on GPT-OSS 20B)
OpenAI-compatible API for easy integration
Competitive pricing for open-weight models
Free tier available for testing

Considerations

Small model catalog: production text models are limited to OpenAI GPT-OSS
Focus on inference only - no training capabilities
Several models are preview-only and may be discontinued at short notice

Wafer

Advantages

High-throughput serving with results independently benchmarked on Artificial Analysis
Prompt caching with discounted cached-input rates
Dedicated endpoints set up in under 24 hours
Runs across NVIDIA, AMD, and AWS Trainium accelerators rather than a single vendor

Considerations

Small serverless model catalog centered on the GLM family
Inference only - no GPU rental, training, or fine-tuning hosting
Early-stage company with a smaller ecosystem than established inference providers

Compute Services

Groq

Wafer

Pricing Options

Groq

Pay-per-token

Token-based pricing with separate input/output rates; audio models are billed per hour and speech models per character

Batch and flex processing

Alternative service tiers for throughput-tolerant or bursty workloads instead of the standard on-demand tier

Enterprise capacity

Dedicated capacity and enterprise-only models quoted through sales

Free tier

Rate-limited free access for development and testing

Wafer

Pay-per-token

Prepaid credits with separate input and output token rates per model and no subscription

Cached input

Reduced rates for cached input tokens on supported models

Dedicated endpoints

Custom pricing for dedicated deployments with tuned performance targets, arranged with the sales team

Getting Started

Groq

Get Started

1
Create an account
Sign up at console.groq.com with email or OAuth
2
Get API key
Generate an API key from the console dashboard
3
Make API calls
Use the OpenAI-compatible endpoint with your preferred model

Wafer

Get Started

1
Create an account
Sign up at app.wafer.ai and load credits for pay-as-you-go usage
2
Generate an API key
Create a key in the console and pass it as a Bearer token
3
Make your first request
Call the OpenAI-compatible endpoint at pass.wafer.ai/v1 with a model from the serverless catalog

Support & Global Availability

Groq

Global Regions

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

Support

Documentation and API reference, developer community, production readiness guides, and enterprise onboarding via sales

Wafer

Support

Documentation at docs.wafer.ai, email support (hi@wafer.ai), and scheduled onboarding calls for enterprise