This AI model comparison puts current models from Anthropic, OpenAI and Google side by side on context window, input and output price, and key strengths. Sort by any column and filter by provider to find the right model for your task and budget — Claude vs GPT vs Gemini, at a glance.
There is no single “best” model; the right choice depends on the work, the volume and how much you’re willing to spend.
How to choose an AI model
For the hardest reasoning, long agentic workflows and high-stakes output, the flagship models win. For high-volume, latency-sensitive or cost-sensitive work, the smaller models are dramatically cheaper and usually good enough. Sort by price to find the cheapest option that clears your quality bar, or by context window if you need to fit large documents.
Context window, price and speed
The context window is how much text a model can consider at once — a 1M-token window holds roughly 750,000 words. Input and output prices are quoted per million tokens, with output typically costing several times more than input. Smaller models are also faster, which matters for interactive and real-time features.
Frontier vs small models
A common pattern is to route most traffic to a small, cheap model and escalate only the hard cases to a frontier model. This “model routing” keeps costs low without sacrificing quality where it counts. The figures here are last verified at the date shown under the table, with links to each provider for the current numbers.