What is the difference between Beam and EcoHash?

Beam and EcoHash 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: Beam or EcoHash?

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 Beam and EcoHash?

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 4 different GPU models across both Beam and EcoHash, with 0 models available from both providers.

Beam vs EcoHash

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

Beam

Provider 1

GPUs Available

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EcoHash

Provider 2

GPUs Available

Visit Website

Comparison Overview

Total GPU Models

Beam GPUs

EcoHash GPUs

Direct Comparisons

GPU Pricing Comparison

Total GPUs: 4Both available: 0Beam: 3EcoHash: 1

Showing 4 of 4 GPUs

Last updated: 10/6/2026, 9:52:40 AM

GPU Model ↑	Beam Price	EcoHash Price	Price Diff ↕	Sources
H100 SXM 80GB VRAM • Beam	$3.50/hr★ Best	Not Available	—	Beam
H100 SXM 80GB VRAM • Beam $3.50/hour Updated: 10/1/2026 ★Best Price Not Available Beam
RTX 4090 24GB VRAM • Beam	$0.69/hr★ Best	Not Available	—	Beam
RTX 4090 24GB VRAM • Beam $0.69/hour Updated: 10/1/2026 ★Best Price Not Available Beam
RTX 5090 32GB VRAM • Beam	$1.09/hr★ Best	Not Available	—	Beam
RTX 5090 32GB VRAM • Beam $1.09/hour Updated: 10/1/2026 ★Best Price Not Available Beam
RTX PRO 6000 96GB VRAM • EcoHash	Not Available	$1.89/hr★ Best	—	EcoHash
RTX PRO 6000 96GB VRAM • Not Available EcoHash $1.89/hour Updated: 10/6/2026 ★Best Price EcoHash

H100 SXM 80GB VRAM • Beam	$3.50/hr★ Best	Not Available	—	Beam
H100 SXM 80GB VRAM • Beam $3.50/hour Updated: 10/1/2026 ★Best Price Not Available Beam
RTX 4090 24GB VRAM • Beam	$0.69/hr★ Best	Not Available	—	Beam
RTX 4090 24GB VRAM • Beam $0.69/hour Updated: 10/1/2026 ★Best Price Not Available Beam
RTX 5090 32GB VRAM • Beam	$1.09/hr★ Best	Not Available	—	Beam
RTX 5090 32GB VRAM • Beam $1.09/hour Updated: 10/1/2026 ★Best Price Not Available Beam
RTX PRO 6000 96GB VRAM • EcoHash	Not Available	$1.89/hr★ Best	—	EcoHash
RTX PRO 6000 96GB VRAM • Not Available EcoHash $1.89/hour Updated: 10/6/2026 ★Best Price EcoHash

LLM API Pricing Comparison

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

Showing 13 of 13 models

Prices per 1M tokens · Last updated: 10/6/2026, 9:52:40 AM

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

Features Comparison

Beam

Pay-per-millisecond Billing
Only charged when your code runs, no charges for cold starts or server spin-up
Sub-second Cold Starts
Memory snapshots and GPU checkpoint restore bring containers back in seconds, which Beam reports as up to 35x faster than a traditional cold boot
Secure Sandbox Environments
Run untrusted code safely in isolated environments for AI agents and code interpreters
Stateful, Persistent Runtimes
Pause and resume sessions while maintaining filesystem, memory, and running processes
Elastic GPU Scaling
Scale to zero when idle, burst to thousands of containers in seconds
Custom Docker Images
Bring your own Docker images for full environment control, including running the Docker daemon inside containers

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.

Pros & Cons

Beam

Advantages

Pay-per-millisecond billing with no charges for cold starts
Ultrafast boot times with sub-second cold starts via memory snapshots
GPU selection spanning RTX 4090 through B200, plus InfiniBand cluster nodes
On-demand machines priced flat per machine, including vCPU, RAM, and NVMe storage

Considerations

Serverless GPUs other than the RTX 4090 require a committed-spend agreement
GPU container concurrency is capped on the lower plan tiers
Multi-node InfiniBand clusters are sales-only with no published pricing

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

Compute Services

Beam

Inference Endpoints

Deploy high-performance inference endpoints with custom models

Custom model hosting on GPU or CPU
Pre-loading models for fast response times

Sandboxes

Secure code execution environments for AI agents

Run untrusted LLM-generated code safely
Snapshot and restore complete system state

Task Queues

Run large-scale workloads with distributed processing

Audio processing pipelines
Data processing at scale

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.

Pricing Options

Beam

Pay-per-millisecond

Serverless GPU, CPU, and sandbox usage billed by the millisecond with no minimum charges

Committed Spend

Serverless access to GPUs beyond the RTX 4090 is arranged through a committed-spend agreement

On-Demand Machines

Flat hourly price per machine that already includes the vCPU, RAM, and NVMe storage

Reserved Clusters

Multi-node InfiniBand clusters reserved monthly or yearly, quoted through sales

Bring Your Own Cloud

Per-vCPU and per-GB management fee on top of compute billed directly by your own cloud provider

Storage

Persistent volumes and snapshots included up to a capacity threshold, then billed per GB per month

Monthly Plans

Developer plan free with usage, Team plan with a monthly base fee plus usage, and a contact-sales Growth tier

Free Monthly Credits

All plans include monthly free credits that refresh each month

Volume Discounts

Discounts available for high monthly usage, arranged through sales

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

Getting Started

Beam

Get Started

1
Create an account
Sign up on the Beam platform to receive monthly free credits
2
Set up Python environment
Create a virtual environment and install the Beam SDK
3
Authenticate with API token
Configure your API token to connect to Beam
4
Deploy your first app
Run a function locally, then deploy it as a web endpoint with the Beam CLI

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.

Support & Global Availability

Beam

Global Regions

30+ regions spanning the US, EU, Asia-Pacific, and Canada, with workloads routed across clouds and regions in real time

Support

Documentation, public Slack community, and a status page; live chat support on paid plans and a private Slack channel on the top tier

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.