[AINews] Claude Haiku 5.5 — better than GPT-6 Luna at the same pricing
Source
latent.space
Date
Why it matters
Haiku 5.5 is Anthropic's cheapest and fastest model, about 75% cheaper per task than Haiku 4.5, priced to match GPT-6 Luna. Sonnet 5.5 and subscription prices were also cut, changing cost choices for multi-agentUsing several AI agents on one problem — splitting work in parallel, checking each other, or filling different roles like planner and reviewer.Full definition → workloads.
Key takeaways · AI-distilled
Haiku 5.5 costs $0.10/$0.50 per 1M input/output tokenThe chunk of text a model reads and writes in — roughly three-quarters of a word — and the unit AI usage is billed in.Full definition → under 100K prompt tokens, but five times that above 100K; AINews suggests this step plus heavy token use explains why Cursor's 10x claim differs from Anthropic's 75% average.
Artificial Analysis found Haiku 5.5 uses about 162k output tokens per Index task at max effort, roughly 3x GPT-6 Luna, and even at an equal score of 38 it is somewhat more verbose, so per-token savings are partly offset.
On AA-Omniscience, Haiku 5.5 scored 36% accuracy with a 40% hallucinationWhen a model states something false with full confidence — inventing facts, citations, or APIs that don't exist.Full definition → rate, versus Luna's 44% and 77%; the newsletter says part of the lower accuracy comes from the model more often saying it does not know.
Its 35% AutomationBench-AA score trails Luna and other small models at 53 to 60%, but a pre-release safety bug made it over-refuse; Anthropic is fixing it and Artificial Analysis expects the score to rise on a re-run.
Alongside the launch, Anthropic built computer-use and browser-use toolsets into its Python and TypeScript SDKs, which now run the action loop and send clicks and keystrokes to drivers such as Browserbase, E2B or Daytona.
Terms in this piece · Glossary
multi-agent — Using several AI agents on one problem — splitting work in parallel, checking each other, or filling different roles like planner and reviewer.
token — The chunk of text a model reads and writes in — roughly three-quarters of a word — and the unit AI usage is billed in.
hallucination — When a model states something false with full confidence — inventing facts, citations, or APIs that don't exist.
