Sonnet 5 vs Haiku 4.5
| Input / MTok | $3 vs $1 |
|---|---|
| Output / MTok | $15 vs $5 |
| Context window | 1,000K vs 200K |
| Min cacheable prefix | 1,024 vs 4,096 tokens |
| Effort levels | low, medium, high, xhigh, max vs none |
The comparison that decides most high-volume workloads
This pairing matters most for exactly the workloads where per-token cost compounds fastest — high-volume, repetitive integrations where the difference between these two rates multiplies across enormous request counts. Haiku 4.5 is the cheaper, faster option with no effort parameter at all; Sonnet 5 costs more per token but brings genuine reasoning depth and the full current effort range, including its newest top tier.
Segmenting rather than choosing one for an entire workload
Many real workloads aren't uniform enough to need one answer here — a pipeline that routes its easy, high-volume majority to Haiku and its harder, lower-volume minority to Sonnet often outperforms committing the whole workload to either model alone, capturing most of the cost benefit on the easy cases without sacrificing quality on the ones that genuinely need it.
Measuring where your workload's actual difficulty falls
Before committing to a split, measure where your real task distribution actually falls rather than guessing — a workload that seems evenly split between easy and hard cases at a glance is often more lopsided than it appears once you look at real volume, and that skew should drive which model handles the larger share by default.
Related
See the model picker for a task-specific recommendation, and Sonnet 5 vs Fable 5 for how Sonnet compares at the other end against the lineup's most capable option.
Verified 2026-08-08 against ClaudeHow facts module (src/data/facts/) — see /about/#accuracy.