At a glance
Anthropic ships Claude in three sizes, and picking the right one is the simplest, biggest lever on both quality and your bill. Opus is the most capable model for the hardest reasoning, Sonnet is the balanced workhorse that handles most coding and agent tasks well, and Haiku is the fast, cheap model for high-volume and latency-sensitive work. They share the same core abilities and, in 2026, a 1M-token context at standard pricing; what changes is depth of reasoning, speed and cost per token. This page compares them honestly so you can match the model to the task instead of paying for Opus on work Haiku would nail, or sending a genuinely hard problem to Haiku and getting frustrated. It pairs with our Choosing an AI Model article. Prices are list rates as of 2026 and move over time.
The options
Side by side
| Dimension | Claude Opus | Claude Sonnet | Claude Haiku |
|---|---|---|---|
| Tier | Most capable | Balanced | Fastest and cheapest |
| Best for | Hardest reasoning, architecture, complex refactors | Most coding and agent work | High volume, simple tasks, latency-sensitive work |
| Relative capability | Highest | High | Good for its size |
| Relative speed | Slowest | Fast | Fastest |
| Input price per million (as of 2026) | About USD 5 | About USD 3 | About USD 1 |
| Output price per million (as of 2026) | About USD 25 | About USD 15 | About USD 5 |
| Context window (2026) | 1M tokens at standard pricing | 1M tokens at standard pricing | Large context |
The verdict
Make Sonnet your default: it handles the large majority of coding and agent work at a strong quality-to-cost ratio, which is why Claude Code defaults to it. Reach for Opus on the genuinely hard problems, complex reasoning, tricky refactors and architecture, where its extra depth pays for itself by getting things right the first time. Drop to Haiku for high-volume, simple or latency-sensitive work like classification, extraction and read-only subagents, where speed and cost matter more than peak reasoning. A great pattern is to mix them: a stronger model leads while Haiku does the cheap, narrow side work. To cut spend further, use prompt caching for repeated context and batch processing for non-urgent jobs. When in doubt, start on Sonnet and only move up or down when a task clearly demands it.