Product & chips · Aug 17, 2026

The default setting is the real behaviour: a good laptop-class model treats "draw a circle" as a major commission.

Product moves · This week (event date 08-16)

From the Aug 17, 2026 daily brief

Simon Willison (see Named commentary) tested Alibaba's newly released Qwen 3.8 27B — Apache 2 licence, open weights, vision-capable, about 17GB once quantised to lower precision, which fits a sensibly specified laptop — and rates it among the best local models available on laptop-class hardware. But it ships with reasoning effort set to the highest of its four levels. On the same prompt — the vector drawing of a pelican riding a bicycle he has used as a fixed test for years — reasoning on took 21 minutes and burned 22,276 reasoning tokens, while reasoning off took 137 seconds, a difference of roughly 9.2x. ⚠️ The two runs produced output of similar length (3,223 tokens against 3,715); the whole difference sits in the reasoning segment. The extreme case came from the prompt "draw an svg of a circle," where the reasoning trace opens by talking itself into "concentric guide circles (like a compass/geometry drawing), tick marks, a soft gradient fill on the main circle, restrained ambient motion (a slowly rotating dashed ring, pulsing glow)." A second trap misleads people: the local runner he used defaults to a context limit of 8,192 tokens, which the thinking alone exhausts, and raising it to the full 262,144 made the problem disappear (the full write-up). Two things to do today: when you run a local model, turn the reasoning effort down and raise the context limit to its maximum. Those two defaults decide the behaviour you actually get — four documented levels do not mean users receive four levels. ⚠️ This is one developer's first-hand test rather than a benchmark run. Qwen's own reported numbers show gains over both the previous generation and its own closed-weight model. ⚠️ Those are vendor-reported, with no independent verification yet.

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The default setting is the real behaviour: a good laptop-class model treats "draw a circle" as a major commission.

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More in this section

Customers of chip-design tool vendors have started capping tokens engineer by engineer — and a year ago nobody cared what that line cost.

The new flagship's enterprise edition went live with its first published prices, and its own account of the mechanism doubles as an audit cost.

OpenAI says its first in-house inference chip delivers 1.5 to 1.9 times the throughput per watt of "the commercial systems tested" — and does not say which systems those were.

Meta launched a personal AI agent called Muse, and the part worth recording is not what it does but that a payment network has written terms for a non-human buyer for the first time.