What is the difference between EcoHash and Wafer?

EcoHash 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: EcoHash 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 EcoHash 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.

How many GPU models are available for comparison?

We track pricing for 1 different GPU models across both EcoHash and Wafer, with 0 models available from both providers.

EcoHash vs Wafer

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

EcoHash

Provider 1

GPUs Available

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Wafer

Provider 2

GPUs Available

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Comparison Overview

Total GPU Models

EcoHash GPUs

Wafer GPUs

Direct Comparisons

GPU Pricing Comparison

Total GPUs: 1Both available: 0EcoHash: 1Wafer: 0

Showing 1 of 1 GPUs

Last updated: 10/6/2026, 11:54:59 AM

GPU Model ↑	EcoHash Price	Wafer Price	Price Diff ↕	Sources
RTX PRO 6000 96GB VRAM • EcoHash	$1.89/hr★ Best	Not Available	—	EcoHash
RTX PRO 6000 96GB VRAM • EcoHash $1.89/hour Updated: 10/6/2026 ★Best Price Not Available EcoHash

RTX PRO 6000 96GB VRAM • EcoHash	$1.89/hr★ Best	Not Available	—	EcoHash
RTX PRO 6000 96GB VRAM • EcoHash $1.89/hour Updated: 10/6/2026 ★Best Price Not Available EcoHash

LLM API Pricing Comparison

Total models: 13Both available: 0EcoHash: 13Wafer: 0

Showing 13 of 13 models

Prices per 1M tokens · Last updated: 10/6/2026, 11:54:59 AM

Model ↑	EcoHash	Wafer	Input Diff ↕
DeepSeek V4 Pro DeepSeek	$0.910 in $2.72 out	Not available	—
GLM-5.2 Zhipu	$1.00 in $3.00 out	Not available	—
GLM-5.3 Z AI	$1.25 in $4.30 out	Not available	—
GPT-OSS-20B OpenAI	$0.050 in $0.200 out	Not available	—
Kimi K3 Moonshot	$2.00 in $12.00 out	Not available	—
Llama 3.1 8B Meta	$0.100 in $0.100 out	Not available	—
MiniMax-M3 MiniMax	$0.200 in $0.900 out	Not available	—
Qwen 3 Coder 30B Alibaba	$0.100 in $0.300 out	Not available	—
Qwen 3.8 Flash Alibaba	$0.090 in $0.370 out	Not available	—
Qwen 3.8 Max Alibaba	$1.90 in $5.70 out	Not available	—
Qwen3 Omni 30B A3B Alibaba	$0.400 in $0.800 out	Not available	—
Qwen3 VL 8B Alibaba	$0.150 in $0.500 out	Not available	—
Qwen3.6 35B A3B Alibaba	$0.400 in $0.400 out	Not available	—

Features Comparison

EcoHash

RTX PRO 6000 GPU Instances
Containerized Linux instances with 1, 2, 4 or 8 RTX PRO 6000 GPUs, with root access, SSH, a browser terminal and Jupyter.
GPU Clusters
Clusters of 2–8 identical replicas launched as one unit.
Per-Second Billing
GPU instances are billed per second of running time at one per-GPU rate across instance, dedicated-inference and cluster workloads.
OpenAI-Compatible Inference API
Pay-per-token access to platform models for chat, embeddings, reranking, image generation, speech-to-text, text-to-speech, voice cloning and video generation at api.ecohash.com.
Dedicated Inference
Deploy a Hugging Face or registered model as a managed endpoint called through the same API and key.
Managed Fine-Tuning
LoRA/QLoRA fine-tuning jobs on 1, 2 or 4 GPUs, billed per minute, with a dataset registry that validates JSONL before any GPU is booked.

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

EcoHash

Advantages

Per-second billing with a single per-GPU rate across instance sizes
96 GB of VRAM per GPU on Blackwell-generation RTX PRO 6000 cards
One OpenAI-compatible API for platform models and dedicated endpoints
Covers GPU rental, fine-tuning and inference on one account

Considerations

Single GPU model (RTX PRO 6000); no H100, H200 or B200 capacity
GPU instances available in the United States only
Fine-tuning limited to LoRA/QLoRA jobs on up to 4 GPUs

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

EcoHash

RTX PRO 6000 GPU Instances

Containerized Linux GPU instances with SSH, web-terminal and Jupyter access, billed per second at the same per-GPU rate for every size.

Wafer

Pricing Options

EcoHash

GPU instances

Per GPU-hour, billed per second of running time

Inference API

Per token for language models and per second for some media models, with no minimum commitment

Dedicated Inference

Per GPU-hour for the GPUs behind the endpoint

Fine-tuning

Per minute of GPU time

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

EcoHash

Get Started

1
Create an account
Sign up at console.ecohash.com.
2
Create an API key
Generate a key in the console for the inference API and dedicated endpoints.
3
Call a platform model
Point an OpenAI SDK client at https://api.ecohash.com/v1 and choose a model from the catalog.
4
Launch a GPU instance
Pick a compute template and a 1, 2, 4 or 8 GPU size, then connect over SSH, the browser terminal or Jupyter.

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

EcoHash

Global Regions

GPU instances: United States. Inference API: multi-region routing.

Support

Documentation at docs.ecohash.com and a contact form on ecohash.com; an SLA is published on the website.

Wafer

Support

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