What GPU types does Wafer offer?

Wafer offers various GPU types including . Check the pricing table above for current availability and pricing.

How do I get started with Wafer?

Create an account, Generate an API key, Make your first request

What are Wafer's main advantages?

Wafer's main advantages include: 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.

What are Wafer's limitations?

Wafer's main limitations include: 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.

Wafer

The fastest open source LLMs for enterprise

Inference specialist🇺🇸 USinferencellmopen-source

Last reviewed Jul 7, 2026

Wafer is a San Francisco-based inference provider serving open-source LLMs through a serverless API and dedicated endpoints. Its platform uses AI agents to profile workloads and optimize the model, serving engine, kernel, and hardware combination for each deployment.

Visit Wafer Documentation

We're actively tracking prices for Wafer. Check back soon, or browse other providers with current pricing.

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Pros & Cons

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

Limitations

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

Key Features

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-Compatible API

Standard chat completions endpoint at pass.wafer.ai/v1 with Bearer token authentication

Prompt Caching

Cached input tokens are billed at reduced rates on supported models

Pricing Options

Option	Details
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

Availability & Support

Support

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

Getting 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