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GPT-6 Astra Designed a Device: OpenAI's Hardware Push

At a glanceQuick answers
What did Astra design?
A prototype device for talking to Codex: its look, enclosure, circuit board, interface and firmware, per OpenAI.
Was it production-ready?
No. Manufacturing still took several rounds of human review; Astra missed production limits, tolerances and assembly details.
How does Astra score on CAD work?
0.59 on BenchCAD 2.0 Core at max effort, just ahead of Claude Opus 5.5 at 0.57, per BenchCAD’s October table.
Editorial data illustration on a near-white ground: a small handheld gadget shown exploded into a teal shell, a circuit board and a screen of code, beside a large navy figure 23x for token use on OpenAI's hardware teams
Fig 0One model, every layer of the device. Made by CellCog's image agent, running GPT Image 2.5.

OpenAI said on November 3, 2026 that its models are now helping engineers design, simulate and build physical products. The headline test: two OpenAI team members used GPT-6 Astra to design a device for talking to Codex, enclosure, circuit board and software included, as a side project. OpenAI framed the goal as “seeing if we can create a device without any direct human edits.”

The same post reports a 23-fold rise in token use across OpenAI’s hardware teams since February, a BenchCAD 2.0 score from an unreleased model, and engineering work with Chip Ganassi Racing and Mazda. Here is what Astra did, where it fell short, and how the benchmark numbers compare with Claude Opus 5.5.

On this page · 7 sectionsOpen
  1. What Astra designed
  2. Where it fell short
  3. OpenAI’s own hardware teams
  4. BenchCAD 2.0: what the scores say
  5. Chip Ganassi Racing and Mazda
  6. What it means
  7. Sources
Key points5 · 6 min full read
  1. A small gadget pulled apart into its shell, board and screen.
    OpenAI says two staff used GPT-6 Astra to design a device for talking to Codex, enclosure, circuit board, interface and firmware included, in under a week as a side project.
  2. A caliper measuring a part, with a small warning mark: tolerances missed.
    Getting it manufactured took several rounds of review: Astra did not reliably account for production limits, tolerances or assembly details.
  3. A short bar beside a very tall bar: usage multiplied.
    Token use across OpenAI’s hardware teams has grown 23-fold since February, for CAD models, manufacturing drawings and simulation setup.
  4. Two scoring bars side by side, one slightly taller: a close benchmark race.
    On BenchCAD 2.0, OpenAI says a newer internal model scored 0.875 against 0.594 for Astra; BenchCAD’s public table has Astra at 0.59 and Claude Opus 5.5 at 0.57.
  5. A race car outline with airflow lines over its nose.
    OpenAI is turning 3D scans into editable CAD with Chip Ganassi Racing and starting research on vehicle aerodynamics and crash safety with Mazda.

§ 01What Astra designed

OpenAI split the device work into four disciplines and says Astra handled each one.

Discipline What Astra did
Look and feel Developed the design, drawing on OpenAI’s Work Louder collaboration and references from games and toys
Mechanical Designed the enclosure and the internal structures that hold the parts in place
Electrical Selected the components and laid out the printed circuit board to fit the enclosure
Software Designed the interface and generated the firmware and the Codex integrations
Table 1What GPT-6 Astra did on the test device, per OpenAI (November 3, 2026)

The timeline is the striking part. In OpenAI’s words: “Two team members designed this test device with Astra in under a week while working on it as a side project.” Then: “A contract manufacturer built a small batch of prototypes in under a month.”

Animation: a GPT-6 Astra badge fills four lanes, Look, Enclosure, Circuit board and Firmware, which stack into a device designed in under a week; then a Manufacturer box sends back three amber flags, Tolerances, Production limits and Assembly, and a Review figure turns each one grey after several rounds of review
Fig 1Astra designed every layer fast; people closed the manufacturing gaps

§ 02Where it fell short

Getting the device ready for manufacturing still took “several rounds of review and iteration”, OpenAI says. Astra did not reliably account for the manufacturer’s production limits, tolerances or assembly details, and OpenAI says those gaps are showing what future models need to do better.

So the no-edits test covered the design files. The move from a design to something a factory can build still ran through people.

§ 03OpenAI’s own hardware teams

The broader number is about OpenAI itself: “Since February, model usage across our hardware teams, measured in tokens, has grown 23-fold.” Those teams use Codex and ChatGPT to create and revise CAD models, prepare manufacturing drawings, set up simulations and review designs, across robotics and compute infrastructure.

Grace Lam, a Forward Deployed Engineer at OpenAI, put it this way: “Codex has dramatically accelerated how we move from an idea to an engineered part.”

§ 04BenchCAD 2.0: what the scores say

OpenAI also reports a benchmark jump. On BenchCAD 2.0, a newer internal model averaged 0.875, against 0.594 for GPT-6 Astra at its highest reasoning setting, about 47% higher. OpenAI does not name that model or say when it ships, and the figure is OpenAI’s own.

BenchCAD 2.0, published October 12, 2026, tests whether models can build 3D parts and assemblies from engineering drawings or renders and recover circuit wiring from images of boards. Its Core set is 100 held-out cases, scored against references “without an LLM judge”. On its public table, Astra holds the top published score.

Model Score Cost per case Median time per case
GPT-6 Astra 0.59 $11.05 62 min
Claude Opus 5.5 0.57 $27.58 224 min
Claude Sonnet 5.5 0.41 $43.33 372 min
Claude Fable 5.1 0.30 $48.46 191 min
Claude Haiku 5.5 0.18 $8.69 459 min
Table 2BenchCAD 2.0 Core at maximum reasoning effort (BenchCAD, October 12, 2026)
BenchCAD 2.0 Core score at max effort (BenchCAD, October 12, 2026)Bar chart of BenchCAD 2.0 Core scores at max effort: GPT-6 Astra 0.59 highlighted, Claude Opus 5.5 0.57, Sonnet 5.5 0.41, Fable 5.1 0.30, Haiku 5.5 0.18GPT-6 Astra0.59Claude Opus 5.50.57Claude Sonnet 5.50.41Claude Fable 5.10.30Claude Haiku 5.50.18BenchCAD 2.0 Core score at max effort (BenchCAD, October 12, 2026)Bar chart of BenchCAD 2.0 Core scores at max effort: GPT-6 Astra 0.59 highlighted, Claude Opus 5.5 0.57, Sonnet 5.5 0.41, Fable 5.1 0.30, Haiku 5.5 0.18GPT-6 Astra0.59Claude Opus 5.50.57Claude Sonnet 5.50.41Claude Fable 5.10.30Claude Haiku 5.50.18
Fig 2BenchCAD 2.0 Core score at max effort (BenchCAD, October 12, 2026)

Astra and Opus 5.5 are close on score, but Opus 5.5 spent about 2.5 times the cost and 3.6 times the median time per case to get there. The best published score is still well under 1, which is the point of the benchmark: hardware CAD is hard for every model today.

§ 05Chip Ganassi Racing and Mazda

OpenAI is expanding its work with Chip Ganassi Racing’s R&D team to turn 3D scans of existing parts into editable CAD models and 2D manufacturing drawings, useful when the original design files are gone. Matthew Ortman, an R&D engineer there: “The model has been useful for going from raw scan data to a solid body.”

The new partner is Mazda. OpenAI’s research and Forward Deployed Engineering teams are working with Mazda’s aerodynamics and crash-safety engineers, using simulations of airflow and structural behavior to explore vehicle designs while accounting for styling and cost. OpenAI says it will share results in the coming months, and it is asking engineers, engineering firms and software vendors to sign up as collaborators.

§ 06What it means

For engineering teams, the useful part today is the work between ideas: drawings, simulation setup, scan-to-CAD and design review, with an engineer checking every output. The device test shows how fast a model can get to a first design. The manufacturing loop shows where people still carry the work.

Our conflict, declared: CellCog’s AI employees run on Claude Opus 5.5, the second row in the table above. We do not use GPT-6 Astra and have no stake in OpenAI.

§ 07Sources

Frequently asked5 questions

Q1What did OpenAI announce on November 3, 2026?

A research post on how its models help engineers design, simulate and build physical products, including a device GPT-6 Astra designed, a 23-fold rise in hardware-team token use, BenchCAD 2.0 scores, and work with Chip Ganassi Racing and Mazda.

Q2Did GPT-6 Astra really design a device with no human edits?

OpenAI says it tested whether Astra could create a device without any direct human edits, and Astra designed the enclosure, circuit board, interface and software. Readying it for manufacturing still took several rounds of review and iteration.

Q3What is BenchCAD 2.0?

A benchmark for hardware engineering: building 3D parts and assemblies from drawings or renders, and recovering circuit wiring from images of boards. Its Core set is 100 held-out cases scored against references without an LLM judge.

Q4Which model scores highest on BenchCAD 2.0?

On BenchCAD’s public table from October 12, 2026, GPT-6 Astra at max effort scores 0.59 and Claude Opus 5.5 0.57. OpenAI says an unreleased internal model scored 0.875; BenchCAD has not listed it.

Q5What is OpenAI doing with Mazda?

A new research collaboration with Mazda’s aerodynamics and crash-safety engineers, using simulations of airflow and structural behavior to explore vehicle designs. OpenAI says it will share results in the coming months.

Published 03 November 2026 All Workflows & use cases →