AI Model Comparison
Every major AI model in one table. Filter by provider, sort by any column, and use the quiz to find the right model for your use case.
Find the right model
| Model | Provider | Context | Input $/M | Output $/M | Tier | Strengths |
|---|
Use the quiz above or filter by provider to find the right model for your use case.
How to choose the right model
There is no single best model. The right choice depends on three factors: your task, your budget, and your latency requirements. A flagship model like GPT-5.4 or Claude Opus 4.5 delivers the best reasoning but costs 10-50x more than a budget model. For high-volume classification or extraction, a nano-tier model at $0.05-0.20/M tokens handles the job at a fraction of the cost.
For a detailed breakdown of when to use which model, see our GPT vs Claude vs Gemini comparison. If you're building agents that need tool use and reasoning, start with a balanced-tier model and estimate costs before committing.
Context window vs. quality tradeoff
Larger context windows (500K-1M tokens) let you process entire codebases or long documents in a single call. But more context doesn't always mean better results. Models can struggle to attend to relevant information when the context is very large. Use the context calculator to plan your budget and avoid oversaturating the window.
Get Insanely Good at AI
Specs are easy to compare. Knowing which model to actually pick for your task is harder. The book teaches you how these models work under the hood, so you stop guessing and start making decisions you can defend.
Get the BookFrequently asked questions
- What is the best AI model in 2026?
- There is no single best model. GPT-5.4 and Claude Opus 4.5 lead on complex reasoning. Gemini 3.1 Pro offers the largest context window at 1M tokens. DeepSeek V3.2 and Llama 4 Maverick provide strong performance at a fraction of the cost. The right choice depends on your task, budget, and latency requirements.
- What is the difference between GPT, Claude, and Gemini?
- GPT (OpenAI), Claude (Anthropic), and Gemini (Google) are competing families of large language models. They differ in pricing, context window size, reasoning capabilities, and API features. GPT-5.4 offers multiple tiers from Nano to flagship. Claude emphasizes safety and long-context performance. Gemini leads on multimodal capabilities and context length.
- How do I choose between a flagship and budget AI model?
- Flagship models (GPT-5.4, Claude Opus 4.5) deliver the best quality but cost 10-50x more per token. Budget models handle high-volume tasks like classification, extraction, and simple generation at a fraction of the cost. Start with a balanced-tier model, then move up or down based on output quality and cost targets.