ModelPriceWatch.com
Last scan 2026-08-09 Models tracked 198 Providers 30 Cheapest paid Granite 4.0 Micro $0.017/Mtok in Every price links to its source

LLM model migration calculator

See exactly what you'd save by switching from your current model to any alternative — with the quality tradeoff from real benchmark data alongside every number. Forced off a dead model? Check the retired & deprecated model tracker for verified shutdown dates and named successors.

Your current setup

0 (no filter)100 (best only)

Your current costs

Select your current model to begin.

MODELPRICEWATCH.COM · 2026-08-09

All alternatives ranked by savings

list prices · savings at your usage

Estimates combine public list pricing with the Vellum benchmark blend. Quality scores are general-purpose — validate against your own evals before switching a production workload. At volume, your real price is usually lower than list: get a vendor-neutral quote →

Select your current model above to see migration options.

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How the migration calculator works

This tool combines two datasets: API pricing (sourced from and linked to official provider pages) and benchmark performance data (aggregated from public leaderboards — see each model page for per-score provenance). When you select your current model, we calculate your exact monthly cost using the input/output token ratio you specify.

For each alternative model, we show:

  • Monthly cost — your projected spend on that model, using your same token usage
  • Monthly savings — how much less (or more) you'd pay vs your current model
  • Quality — the model's average benchmark score (higher = better output quality)
  • Perf/$ — performance per dollar: benchmark score ÷ blended cost per Mtok (higher = better value)
  • Verdict — a quick assessment: "save X%, quality Y% better/worse"

Quality threshold: Use the slider to filter out models below your quality floor. If your current model scores 80 on benchmarks, setting the threshold to 70 will only show alternatives with 70+ scores — ensuring you don't sacrifice too much quality for cost savings.

Important: Benchmark scores are averages across multiple tasks and may not reflect your specific use case. A model with a lower average score might outperform a higher-scored model on your particular workload. Use this tool as a starting point, then test promising candidates on your actual data.