Pacific vs. Runpod Comparison


Pacific Pacific Intelligent Technologies	Runpod	+	+
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About Pacific provides GPU compute rental and modular AI infrastructure for organizations running AI training, fine-tuning and inference. Its catalog offers on-demand dedicated NVIDIA GPU nodes, including H100, H200 and B200 configurations, with larger systems and reserved capacity available by request. Rentals provide SSH access to bare-metal Linux hosts with NVIDIA drivers and CUDA. For longer-term or site-specific needs, Pacific offers reserved single-tenant clusters, managed on-premises deployments, colocation and bridge capacity while a permanent facility is prepared. Its factory-built modules combine compute, networking, cooling and power distribution for customer sites, colocation facilities or other suitable powered locations. Buyers include AI teams and infrastructure operators evaluating training or inference capacity, as well as organizations requiring greater control over compute deployment.		About Runpod offers a cloud-based platform designed for running AI workloads, focusing on providing scalable, on-demand GPU resources to accelerate machine learning (ML) model training and inference. With its diverse selection of powerful GPUs like the NVIDIA A100, RTX 3090, and H100, Runpod supports a wide range of AI applications, from deep learning to data processing. The platform is designed to minimize startup time, providing near-instant access to GPU pods, and ensures scalability with autoscaling capabilities for real-time AI model deployment. Runpod also offers serverless functionality, job queuing, and real-time analytics, making it an ideal solution for businesses needing flexible, cost-effective GPU resources without the hassle of managing infrastructure.
Platforms Supported Windows Not Supported Mac Not Supported Linux Not Supported Cloud Supported On-Premises 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 labs, startups, enterprises, and defense organizations that need NVIDIA GPU compute and AI infrastructure.		Audience Runpod is designed for AI developers, data scientists, and organizations looking for a scalable, flexible, and cost-effective solution to run machine learning models, offering on-demand GPU resources with minimal setup time
Support Phone Support Not Supported 24/7 Live Support Not Supported Online Not Supported		Support Phone Support Not Supported 24/7 Live Support Not Supported Online Supported
API Offers API Not Supported		API Offers API Supported
Screenshots and Videos No images available		Screenshots and Videos View more images or videos
Pricing $2.99/GPU-hour Preview GPU-hour rates are H100 $2.99, H200 $4.49, and B200 $6.14. H100 reserved rates are $2.69/GPU-hour for 7–30 days, $2.54 for 31–90 days, and $2.39 for 91–180 days, by request. B300 and NVL72 pricing is by request. Preview rates are indicative until allocation is confirmed. Free Version Not Supported Free Trial Not Supported		Pricing $0.40 per hour Free Version Not Supported Free Trial Not Supported
Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software		Reviews/Ratings Overall 5.0 / 5 ease 5.0 / 5 features 5.0 / 5 design 5.0 / 5 support 5.0 / 5 Read all reviews
		Pros from Real Users Pros As an AI developer using Runpod for a few months now: it’s been a great platform for training and deploying my models. The ability to launch GPU pods so quickly has made a huge difference in my workflow. Cold-start times are almost instantaneous, which means I spend less time waiting and more time experimenting and iterating on my AI projects. Runpod offers a wide range of GPU options, from NVIDIA’s latest H100s to AMD MI300Xs, which covers everything I need for both research-level experiments and larger scale training jobs. The support for custom containers is excellent, so I can bring my own environment or use the many preconfigured templates. The autoscaling serverless infrastructure adapts perfectly to varying workloads, and the real-time logs and analytics help me understand how my models are performing in production. Security and compliance, including SOC2 certification, give me peace of mind when deploying sensitive models.
Training Documentation Not Supported Webinars Not Supported Live Online Not Supported In Person Not Supported		Training Documentation Supported Webinars Not Supported Live Online Not Supported In Person Not Supported
Company Information Pacific Intelligent Technologies Founded: 2026 United States pacificmachines.com		Company Information Runpod Founded: 2022 United States www.runpod.io
Alternatives OneSource Cloud		Alternatives IONOS Cloud GPU Servers IONOS
GPUBank GPU Compute		Compute with Hivenet Hivenet
CambridgeNexus CambridgeNexus, Inc.		DigitalOcean
Fluidstack		Gemini Enterprise Agent Platform Google
WhiteFiber View All		Intel Tiber AI Cloud Intel View All
Categories Cloud GPU Supported		Categories AI Cloud Providers Supported AI Development Supported AI Fine-Tuning Supported AI Inference Supported AI Infrastructure Supported AI/ML Model Training Supported Auto Scaling Supported Cloud GPU Supported Function as a Service (FaaS) Supported Infrastructure-as-a-Service (IaaS) Supported LLM API Supported Machine Learning Supported ML Model Deployment Supported Serverless Supported

Integrations Amazon Web Services (AWS) Not Supported Codestral Not Supported DeepSeek Coder Not Supported DeepSeek R1 Not Supported Docker Not Supported Dropbox Not Supported EXAONE Not Supported Google Drive Not Supported IBM Granite Not Supported Llama 3 Not Supported Llama 3.2 Not Supported Microsoft Azure Not Supported Mistral 7B Not Supported Phi-3 Not Supported Phi-4 Not Supported PyTorch Not Supported Qwen3 Not Supported TensorFlow Not Supported TinyLlama Not Supported Workers by Delos Not Supported Show More Integrations		Integrations Amazon Web Services (AWS) Supported Codestral Supported DeepSeek Coder Supported DeepSeek R1 Supported Docker Supported Dropbox Supported EXAONE Supported Google Drive Supported IBM Granite Supported Llama 3 Supported Llama 3.2 Supported Microsoft Azure Supported Mistral 7B Supported Phi-3 Supported Phi-4 Supported PyTorch Supported Qwen3 Supported TensorFlow Supported TinyLlama Supported Workers by Delos Supported Show More Integrations View All 31 Integrations
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