LLM Cost Estimator

How it works

Enter input/output tokens per request and monthly volume to see a ranked comparison across major LLM providers.

About LLM Cost Estimator

Informational only — not professional advice. Report an error.

Picking an LLM vendor used to be mostly about quality benchmarks. Now it is also a unit economics decision. The same prompt and completion length can produce monthly bills that differ by 10× or more across models and providers — and that gap shows up fast once you move from a demo with ten test queries to production traffic with thousands of requests per day.

This LLM cost estimator takes one workload profile — input tokens, output tokens, and requests per month — and ranks OpenAI, Anthropic, and Google Gemini presets from lowest to highest estimated monthly cost. Comparison only works when the workload stays constant, so define a representative request first. For example: 2,000 input tokens (system prompt plus RAG chunks plus user query) and 500 output tokens (structured answer), at 50,000 requests per month. Every model in the table is evaluated with those same numbers using list pricing from each provider's preset.

The cheapest row is your starting point for pilots, but validate quality on real eval sets before switching production traffic. Rankings shift when you change the input/output ratio. Output-heavy workloads like long code generation or narrative writing favor models with lower output premiums. Input-heavy workloads like large document Q&A with short answers favor cheap input rates and strong context windows. Mini and flash tiers often win on cost for well-scoped tasks; flagship models remain justified when the cost of an error exceeds the cost of the tokens.

The calculator outputs per-request, monthly, and annual figures for each model. It does not include infrastructure, embedding models, vector databases, or human review — add those separately for total cost of ownership. Latency and rate limits are not priced in the ranking but can force expensive model choices for real-time UX. A cheap model with unacceptable time-to-first-token may push you to a faster tier regardless of what the monthly estimate says.

Use provider-specific calculators when you need editable custom rates, and revisit comparisons whenever you upgrade model versions or renegotiate enterprise agreements. Run shadow traffic on the top two ranked models and measure error rate, latency, and human review cost before cutting over production.

This tool is part of the free Developer collection on FindMeTool. Explore more Developer tools or browse the full tool directory.