EcoHashEcoHash Platform Technology
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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.
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About
HPC-AI is an enterprise AI infrastructure and GPU cloud platform designed to accelerate deep learning training, inference, and large-scale compute workloads with high performance and cost efficiency. It delivers a pre-configured AI-optimized stack that enables rapid deployment and real-time inference while supporting demanding workloads that require high IOPS, ultra-low latency, and massive throughput. It provides a robust GPU cloud environment built for artificial intelligence, high-performance computing, and other compute-intensive applications, giving teams the tools needed to run complex workflows efficiently. At its core, the company’s software focuses on parallel and distributed training, inference, and fine-tuning of large neural networks, helping organizations reduce infrastructure costs while maintaining performance. It is powered in part by technologies such as Colossal-AI, which significantly accelerates model training and improves productivity.
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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
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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
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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.
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Audience
AI developers, researchers, and enterprises that need scalable GPU infrastructure to train and run large machine learning models efficiently
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Support
Phone Support
Not Supported
24/7 Live Support
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Online
Supported
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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API
Offers API
Supported
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API
Offers API
Supported
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Screenshots and VideosNo images available
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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
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Pricing
$3.05 per hour
Free Version
Not Supported
Free Trial
Not Supported
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
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Live Online
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In Person
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
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Company InformationEcoHash Platform Technology
Founded: 2025
United States
ecohash.com
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Company InformationHPC-AI
Singapore
www.hpc-ai.com
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Integrations
Hugging Face
Supported
Claude Code
Supported
Codex CLI
Supported
Docker
Not Supported
Kubernetes
Not Supported
Model Context Protocol (MCP)
Supported
OpenAI
Supported
PyTorch
Not Supported
TensorFlow
Not Supported
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Integrations
Hugging Face
Supported
Claude Code
Not Supported
Codex CLI
Not Supported
Docker
Supported
Kubernetes
Supported
Model Context Protocol (MCP)
Not Supported
OpenAI
Not Supported
PyTorch
Supported
TensorFlow
Supported
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