# Pricing Models NeevCloud offers flexible pricing models to match your usage patterns and budget requirements. Understanding these models helps you optimize costs while maintaining the compute power you need. ## On-Demand Pricing ### What is On-Demand? On-demand instances are pay-as-you-go GPU resources. You pay only for the hours your instance runs, with no long-term commitment or upfront payment. **How On-Demand Pricing Works:** * Billing starts when your instance is running * You're charged per hour (or per minute with hourly billing) * You can start and delete instances anytime * No minimum usage requirements * No cancellation fees ### When to Use On-Demand On-demand pricing is ideal when you: * **Experiment with different configurations**: Testing various GPU types before committing * **Run sporadic workloads**: Training jobs that happen irregularly * **Need flexibility**: Projects with unpredictable duration * **Develop and prototype**: Initial development before production deployment * **Handle urgent tasks**: Sudden computational needs without waiting for reserved capacity **On-Demand Pricing Example:** If you're training a model and you're not sure how long it will take: * **Instance**: NVIDIA A100 (40GB VRAM) * **Rate**: $2.50/hour * **Training duration**: 6 hours * **Total cost**: $2.50 × 6 = $15.00 You only pay for those 6 hours. If you stop the instance, billing stops immediately. **Cost Management with On-Demand:** * Set up monitoring alerts for long-running instances * Stop instances when not actively computing * Use automated shutdown scripts for completed jobs * Monitor your usage dashboard regularly ## Reserved Instance Pricing ### What are Reserved Instances? Reserved instances are GPU resources you commit to using for a specific period (typically 1 month, 3 months, or 12 months) in exchange for significant discounts. **How Reserved Pricing Works:** * You commit to a specific instance type for a set duration * You pay upfront or monthly for your reservation * Your hourly rate is significantly lower than on-demand * The instance remains available to you during the reservation period * You pay for the reservation whether you use it continuously or not ### Discount Levels Typical savings compared to on-demand pricing: * **1-month commitment**: \~10% discount * **3-month commitment**: \~20% discount * **12-month commitment**: \~35% discount ### When to Use Reserved Instances Reserved instances make sense when you: * **Run continuous workloads**: Training jobs that span days or weeks * **Have predictable needs**: Regular batch processing or inference serving * **Optimize costs for production**: Deployed models serving predictions 24/7 * **Conduct extended research**: Long-term research projects with steady GPU requirements * **Require guaranteed availability**: Critical workloads that need assured capacity **Reserved Pricing Example:** Compare costs for running an instance 24/7 for one month: **On-Demand:** * Instance: NVIDIA A100 (40GB VRAM) * Rate: $2.50/hour * Monthly hours: 730 hours * **Total cost**: $2.50 × 730 = $1,825/month **Reserved (1-month):** * Discounted rate: $2.25/hour (10% savings) * Monthly hours: 730 hours * **Total cost**: $2.25 × 730 = $1,642.50/month **Savings**: $182.50/month (10%) For long-running workloads, reserved instances provide substantial savings. **Important Considerations for Reserved Instances:** * You commit to paying for the full reservation period * If you stop using the instance early, you still pay the full commitment (we can refund the unused commitment when requested) * The instance type and region are locked for the duration * Plan your capacity needs carefully before committing ## Comparing Pricing Models Use this decision framework: **Choose On-Demand if:** * Usage duration is uncertain * You're experimenting or prototyping * Workload is intermittent or unpredictable * You need maximum flexibility * Project may end suddenly **Choose Reserved if:** * You'll use the instance continuously for weeks/months * Workload is predictable and steady * Cost optimization is a priority * You're deploying to production * You have long-term compute requirements ## Billing and Cost Monitoring ### Understanding Your Bill Your NeevCloud bill includes: * Instance hours consumed (by instance type) * Storage costs (for persistent volumes) ### Cost Tracking Tools NeevCloud provides several tools to monitor spending: * **Real-time dashboard**: See current running instances and hourly rates * **Usage reports**: Historical usage broken down by instance and time period * **Cost projections**: Estimated monthly costs based on current usage * **Budget alerts**: Notifications (Email) when spending approaches your defined limits ### Best Practices for Cost Management * **Tag your instances**: Use meaningful names and tags to track costs by project * **Set up alerts**: Configure notifications for unusual spending patterns * **Review regularly**: Check your dashboard weekly to identify idle resources * **Automate shutdowns**: Use scripts to stop instances when jobs complete * **Right-size instances**: Don't over-provision—choose appropriate VRAM and compute * **Use reserved for base load**: Reserve capacity for steady workloads, use on-demand for peaks * **Delete unused storage**: Clean up old snapshots and volumes you no longer need ## Pricing Transparency NeevCloud displays pricing clearly during instance selection: * Hourly on-demand rate shown for each instance * Reserved pricing available in the reservation configuration panel * Estimated monthly costs calculated based on 730 hours (24/7 usage) * Regional pricing differences highlighted You always know your costs before deployment, with no hidden fees or surprise charges. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. 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