LLM Application Cost Calculator: A Model for Procurement and Experimentation

Developer Ajinkya has introduced the AI Cost Calculator—a tool for estimating the actual costs of applications based on large language models. The calculator is designed as a “procurement-grade” model—that is, not a simplified online calculator, but a tool suitable for budget planning in corporate and government projects.

Supported Scenarios

The calculator includes pre-built workload templates, such as:

• geospatial Q&A in various configurations (free-form, multi-segment, with a tool registry);
• agents for government tasks—power grid modeling (DOE), clinical trial search (NIH), storm tracking (NOAA);
• chatbots for startup support, a HIPAA-compliant patient portal, and legal triage;
• benchmarks: SWE-bench single-run coder, multi-agent support, and a voice agent (STT → LLM → TTS).

Hosting Strategies

The key decision is where the model runs. The calculator offers four options:

• API (managed) — pay-per-token via OpenAI / Anthropic / Bedrock, with reservations for committed spend;
• Self-host (EC2 GPUs) — hourly GPU rental for open-source models (Llama, Mistral), with replication and commitment calculations;
• On-prem (owned) — proprietary hardware in a data center, with costs amortized as a fixed monthly amount;
• Hybrid (split) — a combination of API and self-host with customizable traffic allocation.

The choice of hosting strategy changes the entire downstream model: reservation fields appear for the API, GPU instance calculations for self-host, and TCO for on-prem. A mistake at this step can change the final bill by a factor of 5–10.

Global Settings and Export

At the entire workload level, you can configure MAU, sessions, dialogue steps, caching, and repeat requests. Settings specific to individual agents are located in a separate tab. Results can be exported to Excel, CSV, printed, or saved as a PDF, and you can also copy a shareable link.

Source: Hacker News - Newest: ""AI" "LLM""