Claude Haiku 5.5 is cheap. Keep its jobs small

Claude Haiku 5.5, released on 7 October 2026, makes narrowly scoped subagents worth another look. Anthropic charges $0.10 per million input tokens for prompts up to 100,000 tokens, with higher rates above that threshold. My first use would be extracting facts or summarizing files, while leaving difficult implementation work to Sonnet or Opus. [1] [2]

How much does Claude Haiku 5.5 cost?

Haiku’s lowest rates apply to prompts of at most 100,000 tokens. Above that, Anthropic charges five times as much for input, output and caching. The model supports a million-token context window, but that capacity comes with a pricing decision much earlier in the request. [2] [4]

For an illustrative request with 50,000 uncached input tokens and 5,000 output tokens, Haiku’s token bill is $0.0075. At Sonnet’s rates, the same token counts cost $0.15. That twentyfold difference is a rate calculation, not a measurement of equally good completed work.

This makes a bounded lookup interesting even when a larger model owns the full assignment. I would send the relevant files and ask for the specific fact the parent agent needs, rather than give each helper the entire repository. The repository map I use for context management helps define what information belongs in that smaller request.

Why should you recount tokens before switching?

Haiku 5.5 changes the tokenizer, the system that divides text into billable units. Anthropic’s migration guide says the same text produces approximately 30% more tokens than Haiku 4.5, depending on its content. A prompt that fitted the cheap tier under an old estimate can therefore exceed the new threshold. [3]

Consider input that previously counted as 80,000 tokens. If that particular text grows by 30%, it becomes 104,000 tokens. At Haiku 4.5’s $1 input rate, the old input cost $0.08; at Haiku 5.5’s higher tier, the new input costs $0.052. That is a 35% input-cost reduction in this hypothetical example, rather than the 90% suggested by comparing the lowest published rates. Output, caching and tool charges are excluded. [2] [3]

The practical fix is to count the actual request with the new model before estimating savings. I would also inspect how a multi-turn task grows: Anthropic says Haiku 5.5 retains earlier thinking blocks as input, while Haiku 4.5 keeps only the latest turn’s. A long-running helper can accumulate more input than the tokenizer difference alone suggests. [3]

Can Haiku 5.5 replace Sonnet for coding?

Anthropic’s launch results support trying Haiku on smaller jobs, while keeping Sonnet for harder implementation. On Terminal-Bench 4.0, which tests work in a command-line environment, Anthropic reports 39.2% for Haiku 5.5 and 70.6% for Sonnet 5.5. The price gap comes with a substantial capability gap in that evaluation. [1]

I read that as a reason to separate finding information from deciding what to change. A helper could locate the function that validates a setting and return its file path with the relevant lines. Deciding how to change that validation without breaking other callers is a different assignment. I would test those separately instead of giving the cheapest model both jobs by default.

This is the same distinction behind Sonnet 5.5’s effort and task-cost comparison: the lower token price matters only alongside the amount of work and the result. As with other coding benchmark comparisons, I would keep the evaluator and task attached to the score.

What needs checking in an existing Haiku integration?

A migration needs more than a model-name substitution if the old integration sets reasoning or sampling options. Anthropic documents adaptive thinking as the default for Haiku 5.5, with medium effort. Its migration guide also says to remove temperature, top_p and top_k, and to replace the older explicit thinking-budget configuration. [3] [4]

I would review those settings before running a small existing workload through claude-haiku-5-5. Then I would record the actual input and output counts, whether the answer satisfies the request, and how often a stronger model has to redo it. An extraction task should have a checkable answer, such as the exact line and source file, so a plausible summary does not pass merely because it reads well.

Effort belongs in that comparison too. A helper that spends longer reasoning can change both latency and spending. I would start with the documented default, then change it because a repeatable failure calls for more reasoning or because a simple task passes with less. A million-token allowance is no reason to expand a five-file lookup into a repository survey.

Do the new API credits increase Claude Code limits?

No. Anthropic’s monthly API credits fund work on the Claude Platform and are separate from interactive Claude Code usage. Eligible Max 5x subscribers receive $100 per month and Max 20x subscribers $200. Team credits depend on seat types and are pooled, up to $500 per month. Pro subscribers are not eligible. [5]

You claim the credits by linking a Claude Console organization in the web billing settings, after at least seven days on an eligible plan. Unused credit expires at the end of the billing cycle. It does not pay for interactive Claude Code sessions or extra subscription usage, although API-key-authenticated Agent SDK work can qualify under the documented conditions. [5]

That gives an eligible subscriber a way to try a small API-backed helper without treating the credit as a new Claude Code allowance. My first trial would be one repeated lookup with a known answer. I would keep Haiku if it returns that answer reliably and the measured cost, including corrections, stays lower than doing the same work with the parent model.