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How Much To Run AI
$10Starting price
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About How Much To Run AI
The tool calculates the cost of running open AI models such as Kimi, GLM, DeepSeek and Qwen on local or cloud infrastructure. Users select a model, deployment option and usage level to generate an estimate that includes VRAM, hardware, electricity, labor and source assumptions. The calculation uses model parameters, architecture and hardware specifications from official sources and public price references. It accounts for GPU requirements, power consumption, electricity rates, labor costs and facility overheads like PUE. The result is presented with traceable assumptions and source links so teams can validate and discuss the budget. The estimate is intended as a planning tool for build-or-buy decisions and does not include factors such as throughput, concurrency, latency targets or model quality.
Key features
- Model selection from open models (Kimi, GLM, DeepSeek, Qwen)
- Deployment option selection (cloud rental, purchased hardware, existing infrastructure)
- Usage level presets (light, medium, heavy)
- VRAM and hardware matching based on model size
- Electricity cost calculation with adjustable rates and PUE
- Labor cost estimate based on regional salary ranges and FTE share
- Shareable configuration links and exportable reports (PNG, PDF, Excel, HTML)
- Traceable assumptions and source links for each price entry
Use cases
- Evaluating self-hosting costs for AI model deployment
- Comparing cloud versus on-premises hosting expenses
- Budget planning for AI infrastructure in build-or-buy discussions
Pros
- Provides detailed cost breakdowns including VRAM, hardware, electricity and labor
- Uses verifiable data sources such as official model documentation and hardware vendor specifications
- Allows adjustment of regional and facility-specific inputs like electricity rates and labor salaries
- Generates shareable configuration links and exportable reports
- Covers multiple deployment options including cloud rental, purchased hardware and existing infrastructure
Cons
- Does not model throughput, concurrency or latency targets
- Excludes production requirements such as redundancy, incident response and compliance
- Advanced capacity inputs like context length and concurrency are planned but not yet available
- Estimates are not vendor quotes and may change due to provider, region or contract variations
Frequently asked questions about How Much To Run AI
What does How Much To Run AI calculate?
It estimates the cost of running open AI models like Kimi, GLM, DeepSeek, and Qwen on local or cloud infrastructure, including VRAM, hardware, electricity, labor, and source assumptions.
Who should use this tool?
Teams evaluating build-or-buy decisions for AI deployment, including engineers, managers, and finance stakeholders planning infrastructure budgets.
Does the tool include cloud pricing?
Yes, it incorporates public cloud prices from AWS, Google Cloud, and Microsoft Azure alongside local hardware references.
Can I adjust assumptions like electricity rates or labor costs?
Yes, users can modify exchange rates, electricity rates, salary ranges, FTE shares, PUE, system multipliers, and depreciation periods to match regional and facility conditions.
What factors does the estimate leave out?
It excludes throughput, concurrency, latency targets, model quality, migration, fine-tuning, security, compliance, and application development costs.
How are model and hardware prices sourced?
Model parameters and hardware specs are drawn from official documentation and Hugging Face, while prices use published public references with update times and source links.
