Haiku 5.5 looks interesting. But when is a smaller model enough?

I work around AI API usage, so whenever a new model launches, I tend to look at the cost side first.

Haiku 5.5 caught my attention this month. Anthropic is positioning it as a fast, cheaper option for everyday tasks like summaries and classification, while keeping Sonnet and Opus as stronger choices for complex coding.

That sounds like a useful trade-off. A short summary probably doesn’t need the same model as a difficult debugging session.

But the question I keep coming back to is: how much fixing does the cheaper answer need?

If it gets the job done on the first try, great. If you have to rewrite the prompt twice, check every detail, and eventually switch models, the savings start looking less convincing. Especially when your own time is involved.

That’s the part I’d want to test before moving work over to Haiku 5.5: ordinary, slightly messy requests, not just carefully written examples.

For anyone using it already: what tasks have you comfortably moved to Haiku, and what still sends you back to a bigger model?