Claude Haiku 5.5 and the Steps That Just Became Worth Automating

Anthropic released Claude Haiku 5.5 on October 7, 2026. The number that matters for business automation isn't a benchmark. It's the price: $0.10 per million input tokens and $0.50 per million output tokens for prompts under 100,000 tokens. Anthropic's own comparison puts that at roughly 75% cheaper to run than Haiku 4.5, and a twentieth of Sonnet 5.5 ($2 and $10), which itself shipped September 28 at a price unchanged from Sonnet 5.

We wrote in September about how we pick a model, and the short version was: route the easy steps to a cheap, fast model and save the expensive one for the step that needs reasoning. Haiku 5.5 moves the line for what counts as "easy enough."

What a tenth of a cent buys

Work through one concrete step. A classification prompt that reads an inbound email, a short system prompt and a list of categories might be 1,500 input tokens and 30 output tokens. At Haiku 5.5 rates that's about $0.00016 per email. A business handling 2,000 inbound emails a month pays around 32 cents for the month. The same step on Sonnet 5.5 is roughly $3.30; on Opus 5.5 ($4 and $20 per million) about $6.60.

None of those numbers break a budget. What changes is the steps you'd never have bothered to automate because the per-call cost felt silly against the value:

• Tagging every support ticket by product line and urgency, not just the ones that come through the form.
• Checking every new CRM contact's job title against a list of buyer roles and setting a property.
• Summarizing every meeting transcript into three bullets for the deal record.
• Reading every vendor invoice PDF and flagging the ones where the total doesn't match the PO.

At Haiku 5.5 prices, the model cost of those four workflows combined is likely under what you spend on coffee for the office. The cost that remains is the build, and that was always the bigger line anyway.

Where it isn't the right tool

Anthropic says plainly that Sonnet 5.5 and Opus 5.5 "remain better choices for complex agentic coding tasks," and the published benchmarks show a wide gap on multi-step tool work (Sonnet 5.5 scores 70.6% to Haiku's 39.2% on Terminal-Bench 4.0, per Anthropic's page). We read that as: Haiku 5.5 is for steps with a clear right answer and a short path to it. Classify, extract, summarize, route. Not "look at this deal and decide what to do about it."

Two practical caveats from the pricing page. Prompts over 100,000 tokens cost five times more ($0.50 and $2.50), so stuffing a whole document archive into one call erases the savings. And the model is listed as available on Anthropic's API plus AWS, Google Cloud and Microsoft Azure; if your data has to stay in one of those clouds, confirm the model is live in your region before you plan around it.

How we'd use this in a client stack

The pattern we described in our Claude Code, n8n and Python stack already separates model calls from workflow logic. The model id is a config value. So the practical step is:

1. List every model call in your current workflows with its monthly volume.
2. Mark the ones that are classify, extract or summarize with a fixed output shape.
3. Switch those to Haiku 5.5, keep the previous model's outputs for a week, and compare.
4. Leave the judgment-heavy steps where they are.

In our experience the comparison step is where people get surprised, in both directions. Some steps hold up perfectly on a smaller model. Others degrade in a way that only shows up on the odd inputs: a forwarded email with four quoted replies, a PDF with a scanned page. Run the comparison on a messy sample, not a tidy one.

The bigger shift

A year ago, the model bill was a meaningful line in the automation projects we scoped, and it shaped what got built. For high-volume, low-complexity work it's now close to a rounding error, which puts the decision back where it belongs: on the plumbing, the error handling and the review gates. If you're sizing a project like this, our custom apps page covers how we scope the build side.