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Anthropic Ships Claude Opus 4.8 with Improved Honesty and Cheaper Fast Mode

29 MAY 2026·2 MIN READ·4 SOURCES·Independently corroborated

Anthropic has released Claude Opus 4.8, an incremental update featuring improved factual accuracy, reduced hallucinations, and dynamic workflows capped at 1,000 subagents.

Anthropic Ships Claude Opus 4.8 with Improved Honesty and Cheaper Fast Mode

Key takeaways · 3

  • 01

    Opus 4.8 is four times less likely to allow code flaws to pass unremarked.

  • 02

    A cheaper fast mode is priced at double the standard token rate.

  • 03

    Dynamic workflows are introduced with a cap of 1,000 subagents.

Release and Pricing

Anthropic released Claude Opus 4.8 alongside dynamic workflows that are capped at 1,000 subagents. [2] The company described the update as a modest but tangible improvement over its predecessor. [1] Opus 4.8 maintains the 1,000,000 token context window and January 2026 knowledge cutoff of version 4.7. [1] Standard pricing remains unchanged at $5 per million input tokens and $25 per million output tokens. [1] However, the model introduces a cheaper "fast mode" priced at exactly double the standard rates, which is significantly lower than the $30 and $150 rates for previous versions. [1][2]

Improved Honesty and Accuracy

The model focuses heavily on honesty, with evaluations showing it is around four times less likely than previous models to leave code flaws unremarked. [1] Claude Opus 4.8 achieved the lowest incorrect-rate among the six models tested across every benchmark. [1] This reduction in factual hallucination was primarily achieved by the model abstaining from answering questions when it was uncertain. [1]

This update highlights a shift in AI development from raw capability to reliability and cost efficiency. By prioritizing verifiable accuracy over confident guesswork, models become safer for production environments.

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How this developed

  1. 31 May 2026

    Event evidence refreshed from source cluster.

  2. 29 May 2026

    Event created from source cluster.

Sources

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