AIToday
Large Language ModelsZenn AI/MLPublished: Oct 16, 2026, 10:00 JST

Haiku 5.5 nails every checklist, drops the point

Haiku 5.5 nails every checklist, drops the point

3 Key Points

  1. What happened

    Summarizing the same 14 saved articles, Haiku 5.5 missed the core claim in 4 of 13 cases twice running, while Opus 5.5 managed 13/13 and 12/13; fabricated figures and quotes were 0 under every condition.

  2. Why it matters

    A fact-checking script can only confirm what a summary says, so a missing core claim leaves no signal a reader could notice — and even Opus 5.5 missed one core claim, suggesting silent omission is not purely a cheap-model problem.

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Context & Analysis

The test was set up to isolate the model itself, not the retrieval pipeline. Fourteen web articles were fetched and saved on 10/9, and the identical files were fed to every condition, so differences could not come from CAPTCHA or timeouts changing what each model read.

A line is drawn between two kinds of summary failure. A factual error can be caught by checking what is written against the source. A missing core claim cannot be caught that way, because nothing about it appears in the summary for a checker to compare. The plain-prompt Haiku summaries passed the factual check at full marks in the top row of the comparison table while still dropping the central point in 4 of 13 cases — the failure sits outside the net.

Retrieval limits behaved differently. Opus 5.5, left with the plain prompt, wrote about missing images, truncated bodies, and CAPTCHAs in only 3–4 out of 10 articles, showing that gap is not unique to cheaper models. The prompt step closed both gaps at once, pushing Haiku's core-claim score to 13/13 and both models' retrieval-limit score to 9–10/10. An example was the GPT-6 announcement, where the plain Haiku summary listed every product detail correctly but never mentioned the closing line about software adapting to people; the stepped version put that line at the top and flagged that the interactive UI examples in the fetched text were labeled GPT-5.6 Instant.

FAQ
Did the cheaper model make up facts?
No. Across every condition in the comparison, cross-checking numbers and English quotes against the source text returned 0 fabrications for both Haiku 5.5 and Opus 5.5.
What exactly did the missing step ask the model to do?
Before writing, decide three things for each article: the author's central claim in one sentence, two to three supporting points from the source, and which parts could not be retrieved.
Did the cheaper model run faster or use fewer tokens?
No. Haiku 5.5 with the added step took 232 seconds and 136 seconds across two runs, slower than Opus 5.5's 110–124 seconds, and token use stayed roughly 137k–161k in every condition.

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