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Qwen3.8 27B model accurately adds large numbers and returns results in words

By PulseAugur Editorial · [2 sources] ·

Simon Willison documented an experiment comparing the ability of different AI models to perform addition and express the result in words. Initially inspired by a GPT-4o test from two years prior, Willison re-ran the experiment on local hardware using Qwen3.8 27B. The Qwen3.8 model demonstrated a high degree of accuracy, correctly answering 167 out of 169 one-shot attempts when reasoning was enabled. AI

IMPACT Demonstrates improved numerical reasoning and word-based output capabilities in LLMs.

RANK_REASON The cluster details an experiment comparing AI model capabilities on a specific task, fitting the research category.

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AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Qwen3.8 27B model accurately adds large numbers and returns results in words

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COVERAGE [2]

  1. Simon Willison TIER_1 English(EN) ·

    Qwen3.8 27B addition in words

    <p><strong>Research:</strong> <a href="https://github.com/simonw/research/tree/main/qwen38-addition-in-words#readme">Qwen3.8 27B addition in words</a></p> <p>Colin Frasier <a href="https://bsky.app/profile/colin-fraser.net/post/3mwopbyznhs2k">posted on Bluesky</a> about an experi…

  2. Mastodon — mastodon.social TIER_1 English(EN) · [email protected] ·

    Qwen3.8 27B addition in words https://simonwillison.net/2026/Oct/4/qwen38-addition-in-words/ # AI # LLM # Tech

    Qwen3.8 27B addition in words https://simonwillison.net/2026/Oct/4/qwen38-addition-in-words/ # AI # LLM # Tech

    LINKS simonwillison.net/…/qwen38-addition-in-wo…

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