Anthropic's Haiku 5.5 system card reports 0.870 with tools and 0.670 without on the 1,000-file Vision2Code subset, up from 0.210 and 0.155 for Haiku 4.5. Congratulations to the Anthropic team!
With tools, Haiku 5.5 reaches about 0.79 at roughly $0.25 a task, ahead of every other model in the card at that cost, and 0.870 at under $2.
Anthropic's Sonnet 5.5 system card reports 0.963 with tools and 0.747 without on the 1,000-file Vision2Code subset: first in both settings on our leaderboard, just ahead of Opus 5.5 (0.962 / 0.730) and GPT-6 Astra (0.959 with tools). Congratulations to the Anthropic team!
As in Opus 5.5's card, the score climbs with test-time compute, most steeply with tools: Sonnet 5.5 goes from about 0.33 at under half a cent a task to 0.963 at about $6.
Anthropic's Opus 5.5 system card reports 0.730 without tools and 0.962 with tools on the 1,000-file Vision2Code subset, the highest score published in either setting.
The same card updates Anthropic's earlier models: Fable 5.1 now 0.606 / 0.926, Opus 5 0.497 / 0.899, Sonnet 5 0.322 / 0.519.
OpenAI's GPT-6 Astra launch lists BenchCAD at 0.959 with a Python tool on the 1,000-file Vision2Code subset — the second lead change in three days, after Claude Fable 5.1's 0.843 on September 1.
Two caveats we are keeping visible. OpenAI has published no no-tools figure, so Astra carries an agentic score only and takes no rank in the plain column. And OpenAI notes its own Claude comparison runs “used modified evaluation settings” — the Claude numbers on our leaderboard come from Anthropic's system cards, not from OpenAI's table.
Anthropic's Fable 5.1 system card reports it on BenchCAD's Vision2Code subset — 0.437 without tools and 0.843 with, the highest with-tools score any lab has published, narrowly past GPT-5.6 Sol's 0.834.
Without tools the order is unchanged — Sol still leads 0.706 to 0.437. The whole gain sits in the agentic setting, and it keeps scaling with test-time compute: with tools, Fable 5.1 nearly doubles its own no-tools score.
Anthropic's Opus 5 system card reports it on BenchCAD's Vision2Code subset — 0.366 without tools, 0.821 with — and it upstreams two fixes to our reference (a camera-position typo and raw-shape grading).
The story isn't the single number — it's the slope. On BenchCAD, Claude's scores now scale steeply with test-time compute, especially once the model has tools to crop and verify its own renders. More effort buys markedly more accuracy.
OpenAI lists BenchCAD in its GPT-5.6 launch table, next to OSWorld and BrowseComp — the second frontier lab after Anthropic to report it in a flagship launch, and another sign AI for hardware is now a strategic front.
Scores exactly as printed in OpenAI's launch table (computer-use section, 2026-07-09), self-reported voxel IoU. The Claude bars are Anthropic's own published figures, republished by OpenAI. Hover any bar for its source and split.
We're designing the next major version of BenchCAD in the open, and the scope is set: hard cases — real-work, multi-feature parts selected because today's frontier fails them — and a sandboxed Python environment where models render, measure and iterate before submitting, making the “with tools” setting Anthropic already reports a first-class, comparable leaderboard division. Propose a task or family from your domain and help shape the release.
Also in design as its own track: BenchCAD-Assembly — from single parts to multi-part assemblies, scored on assembled geometry. Its call is coming.
read the 2.0 callAnthropic's Sonnet 5 system card reports it on BenchCAD's Vision2Code subset — 0.266 without tools, 0.373 with — another flagship model card measuring on the benchmark.
Anthropic's Claude Fable 5 / Mythos 5 system card evaluates on BenchCAD Vision2Code: their strongest model reaches ~0.38 voxel IoU on the full set, and ~0.65 with Python tools on a 1,000-file subset. The first frontier lab to fold execution-grounded CAD into how it measures its models — an early marker of what has since become a strategic front.
