EcoHashEcoHash Platform Technology
|
Neysa NebulaNeysa
|
|||||
Related Products
|
||||||
About
EcoHash is a cloud platform for AI compute and model serving. It provides on-demand NVIDIA RTX Pro 6000 GPU workspaces and clusters, persistent cloud drives and shared filesystems, dataset validation, managed LoRA and QLoRA fine-tuning, dedicated model endpoints, and an inference API for text, vision, embeddings, reranking, image, and speech workloads. Developers can run their own containers or deploy open models and call platform or dedicated models through an OpenAI-compatible API. A browser console, SSH, JupyterLab, Compute API, and MCP tools support building, training, deploying, and managing workloads. EcoHash serves AI developers and platforms, including startups and cloud providers, and energy and mining operators developing AI compute infrastructure.
|
About
Nebula allows you to deploy and scale your AI projects quickly, easily and cost-efficiently2 on highly robust, on-demand GPU infrastructure. Train and infer your models securely and easily on the Nebula cloud powered by the latest on-demand Nvidia GPUs and create and manage your containerized workloads through Nebula’s user-friendly orchestration layer. Access Nebula’s MLOps and low-code/no-code engines to build and deploy AI use cases for business teams and to deploy AI-powered applications swiftly and seamlessly with little to no coding. Choose between the Nebula containerized AI cloud, your on-prem environment, or any cloud of your choice. Build and scale AI-enabled business use-cases within a matter of weeks, not months, with the Nebula Unify platform.
|
|||||
Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
|
Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
|
|||||
Audience
AI developers and AI platforms—including startups, GPU marketplaces, and cloud providers—building or running AI models. The company also addresses energy and Bitcoin-mining operators interested in supplying infrastructure for AI inference.
|
Audience
Companies looking for an AI platform that provides a containerized GPU environment to deploy and manage your AI/ML workloads
|
|||||
Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
|
Support
Phone Support
Supported
24/7 Live Support
Not Supported
Online
Supported
|
|||||
API
Offers API
Supported
|
API
Offers API
Not Supported
|
|||||
Screenshots and VideosNo images available
|
Screenshots and Videos |
|||||
Pricing
$0.02/1M tokens
Inference API usage starts at $0.02 per million input tokens for Jina-Embeddings-V3; other models and modalities have separate usage rates. RTX Pro 6000 GPU instances, clusters, and dedicated inference cost $1.89 per GPU-hour, billed per second with no minimum commitment. Storage starts at $5 per month for 50 GB; reserved nodes are contract-priced. A $1 signup credit is offered.
Free Version
Not Supported
Free Trial
Not Supported
|
Pricing
$0.12 per hour
Free Version
Not Supported
Free Trial
Not Supported
|
|||||
Reviews/
|
Reviews/
|
|||||
Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
|
Training
Documentation
Not Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
|
|||||
Company InformationEcoHash Platform Technology
Founded: 2025
United States
ecohash.com
|
Company InformationNeysa
www.neysa.ai/nebula
|
|||||
Alternatives |
Alternatives |
|||||
|
|
||||||
|
|
|
|||||
Categories |
Categories |
|||||
Integrations
Claude Code
Supported
Codex CLI
Supported
Hugging Face
Supported
Model Context Protocol (MCP)
Supported
OpenAI
Supported
|
Integrations
Claude Code
Not Supported
Codex CLI
Not Supported
Hugging Face
Not Supported
Model Context Protocol (MCP)
Not Supported
OpenAI
Not Supported
|
|||||
|
|
|