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Public Geekbench 7 results attributed to OpenAI dots show a post-launch multi-core median of about 8,550, roughly six times the reported Meta Muse median of 1,394. But the runs used markedly different virtual-machine allocations: the dots-associated configuration had nine reported CPU cores, while Muse’s had two. The scores compare CPU throughput in a small sample, not the agents’ overall capability.
What the Geekbench 7 results show
Tom’s Hardware reported on September 30, 2026, that it found six post-launch Geekbench 7 runs associated with dots in the public benchmark database. Those runs scored from 8,135 to 8,991 in multi-core testing, with a median of about 8,550. Their single-core scores ranged from 1,512 to 1,614, with a median of 1,570. Tom’s Hardware’s report attributes these figures to its review of the public Geekbench 7 database.
The same report identified a pre-launch dots-attributed result of 9,435 multi-core points. The screenshot was uploaded on September 25, four days before launch, and the person who ran it is unknown. It exceeds the later sample’s best score by nearly 5% and its median by about 10%, so it is useful context but should not be treated as the typical post-launch result.
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How dots compares with Meta Muse
In Tom’s Hardware’s sample, ten Geekbench 7 runs associated with Meta Muse had medians of about 1,041 single-core and 1,394 multi-core points. The reported dots post-launch medians are about 1.5 times Muse’s single-core score and roughly six times its multi-core score.
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| Reported service and sample | Single-core median | Multi-core median | Reported VM configuration |
|---|---|---|---|
| OpenAI dots, six post-launch runs | 1,570 | About 8,550 | Nine-core AMD EPYC 9V74 configuration; 2.6 GHz base clock; 9.73 GB memory |
| Meta Muse, ten runs | About 1,041 | About 1,394 | Two-core AMD EPYC 9D25 configuration; 1.5 GHz base clock; 7.75 GB memory |
The configurations above are those reported or inferred from benchmark-system descriptions in Tom’s Hardware’s coverage, not official infrastructure specifications published by OpenAI or Meta. The report also cites an independent Muse run scoring 1,000 single-core and 1,433 multi-core points, which is close to its ten-run median.
Why the multi-core gap is not an agent-speed verdict
The reported dots configuration has more than four times Muse’s core count, as well as a higher reported base clock. Those allocation differences help explain why the multi-core result is much larger. The figures do not isolate the effect of the agent software, and the report suggests remaining differences may relate to clock speed and processor architecture.
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- Geekbench measures CPU performance: it does not directly test the quality of an agent’s answers or actions.
- These are public uploads, not a controlled comparison: the sample sizes are small, and the machines were not configured alike.
- The results do not establish user-task speed, reliability, or operating cost: none of those outcomes is measured by these scores.
What is known about the dots computer
OpenAI described each dot as having “their own cloud computer, their own browser, and the apps you’ve connected,” as quoted in Tom’s Hardware’s coverage. The reported Geekbench configuration points to a nine-core AMD EPYC 9V74 virtual-machine slice with 9.73 GB of memory, but those details come from public benchmark records and secondary reporting rather than a formal OpenAI hardware disclosure.
Tom’s Hardware also described a launch-day user interaction in which a dot identified Debian Linux and listed applications including Chromium, Blender, GIMP, Inkscape, Kdenlive, Godot, FreeCAD, OpenSCAD, KiCad, QGIS, ParaView, and 3D Slicer, as well as Python, Node.js, and Git. This is one user-reported account, not an official published inventory of every dots environment.
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Availability and remaining unknowns
At launch, Tom’s Hardware reported dots as available to Pro and Business Premium users. Product access can change, so check OpenAI’s current product information before relying on that eligibility. The report also said OpenAI described future plans to let users add dots and increase their speed; it did not establish that these scaling options were already available.
The report does not establish who ran the pre-launch benchmark or whether dots retain the reported CPU cores while idle. Nor does a benchmark system description confirm that every dot receives an identical configuration.
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