When planning LLM usage in business solutions, it is essential to account for the associated costs. This analysis aims to help plan such costs by aggregating prices of the most popular models, their price trends, model performance, and future price forecasts.
Cost model and routing optimization — REAL pricing (OpenRouter API 2026-10-08), REAL benchmarks (LMArena), simulated telemetry
Pricing and specs per tier
Input/output prices per model (USD / 1M tokens) — solid: input, dashed: output
N=8 quarterly points (simulated) + 1 real (2026-10-08, OpenRouter API)
Linear extrapolation. Band ±10%/±20%/±30% at 1/2/3 quarters — heuristic, not statistical.
An interactive calculator — set your task parameters and the router indicates which solution generates the lowest estimated cost per correct answer. Plan routing costs before deployment.
Enter task parameters — router finds optimal model (cost per correct answer)
Breakeven as a function of token volume. Self-hosted = fixed cost (amort + energy), does not scale with tokens.
A look at real per-model usage (simulated 7-day data): requests, tokens, cost, latency and errors. Shows where spend actually goes and where performance bottlenecks are.
Tokens, costs, latency per model
Energy prices in key data center zones + TCO sensitivity analysis
New models appear on the market faster and faster. The chart shows the frequency of new model releases per provider — denser points mean faster development by that company.
Monthly releases per provider
LMArena Elo measures which model users prefer in blind tests. The chart shows how performance (preference) evolves with each new release — you can see whether a company's next model actually raises the bar.
Elo rating per model (LMArena, snapshot 2026-10-08) — points, no smoothing