Google Cloud vs Lambda Labs

Compare GPU pricing, features, and specifications between Google Cloud and Lambda Labs cloud providers. Find the best deals for AI training, inference, and ML workloads.

Google Cloud logo

Google Cloud

Provider 1

0
GPUs Available
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Lambda Labs logo

Lambda Labs

Provider 2

9
GPUs Available
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Comparison Overview

9
Total GPU Models
Google Cloud logo
0
Google Cloud GPUs
Lambda Labs logo
9
Lambda Labs GPUs
0
Direct Comparisons
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Google Cloud
Lambda Labs

GPU Pricing Comparison

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Features Comparison

Google Cloud

  • Compute Engine

    Scalable virtual machines with a wide range of machine types, including GPUs.

  • Google Kubernetes Engine (GKE)

    Managed Kubernetes service for deploying and managing containerized applications.

  • Cloud Functions

    Event-driven serverless compute platform.

  • Cloud Run

    Fully managed serverless platform for containerized applications.

  • Vertex AI

    Unified ML platform for building, deploying, and managing ML models.

  • Preemptible VMs

    Short-lived compute instances at a significant discount, suitable for fault-tolerant workloads.

Lambda Labs

    Pros & Cons

    Google Cloud

    Advantages
    • Flexible pricing options, including sustained use discounts
    • Strong AI and machine learning tools (Vertex AI)
    • Good integration with other Google services
    • Cutting-edge Kubernetes implementation (GKE)
    Considerations
    • Limited availability in some regions compared to AWS
    • Complexity in managing resources
    • Support can be costly

    Lambda Labs

    Advantages
    • Early access to latest NVIDIA GPUs (H100, H200, Blackwell)
    • Specialized for AI workloads
    • One-click Jupyter access
    • Pre-installed popular ML frameworks
    Considerations
    • Primarily focused on AI and ML workloads
    • Limited global data center presence compared to major cloud providers
    • Newer player in the cloud GPU market

    Compute Services

    Google Cloud

    Compute Engine

    Offers customizable virtual machines running in Google's data centers.

    Google Kubernetes Engine (GKE)

    Managed Kubernetes service for running containerized applications.

    • Automated Kubernetes operations
    • Integration with Google Cloud services
    Cloud Functions

    Serverless compute platform for running code in response to events.

    • Automatic scaling and high availability
    • Pay only for the compute time consumed

    Lambda Labs

    Pricing Options

    Google Cloud

    On-Demand

    Pay for compute capacity per hour or per second, with no long-term commitments.

    Sustained Use Discounts

    Automatic discounts for running instances for a significant portion of the month.

    Committed Use Discounts

    Save up to 57% with a 1-year or 3-year commitment to a minimum level of resource usage.

    Preemptible VMs

    Save up to 80% for fault-tolerant workloads that can be interrupted.

    Lambda Labs

    Getting Started

    Google Cloud

    Get Started
    1. 1
      Create a Google Cloud project

      Set up a project in the Google Cloud Console.

    2. 2
      Enable billing

      Set up a billing account to pay for resource usage.

    3. 3
      Choose a compute service

      Select Compute Engine, GKE, Cloud Functions, or Cloud Run based on your needs.

    4. 4
      Create and configure an instance

      Launch a VM instance, configure a Kubernetes cluster, or deploy a function/application.

    5. 5
      Manage resources

      Use the Cloud Console, command-line tools, or APIs to manage your resources.

    Lambda Labs

    Get Started

      Support & Global Availability

      Google Cloud

      Global Regions

      35+ regions and 100+ zones worldwide.

      Support

      Role-based (free), Standard, Enhanced and Premium support plans. Comprehensive documentation, community forums, and training resources.

      Lambda Labs