An independent test found that Qwen3.8 27B running locally on a DGX Spark scored 167 correct out of 169 attempts on large-number addition written out in words when reasoning was enabled, versus far weaker results with reasoning disabled.

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Qwen3.8 27B Addition-in-Words Test on Local DGX Spark Hardware

What happened

FAQ

What exactly did the experiment test?

It tested whether the model could add large numbers and then write the result in words rather than digits, a task that reveals whether the model actually computes or relies on language patterns.

How did enabling reasoning change the results?

With reasoning disabled, errors appeared on larger numbers. With reasoning enabled, the model succeeded in 167 of 169 attempts, though each combination was tested only once.

Should MENA enterprise teams rely on this?

The result is encouraging for running mid-sized models locally on simple arithmetic tasks, but it is a single experiment on a single hardware setup and is not enough for production adoption without internal testing.

Why does local execution on a DGX Spark matter?

Local execution gives full control over the environment and keeps data private, which matters for government and regulated organizations in the region that require in-house data processing.

Source: Simon Willison (LLM & tools)

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