Results for GPT-6 Astra and Gemini Flash 3.8 are just in!
GPT-6 claimed the first spot with a score of 69.3.
Gemini 3.8 Flash on a very solid 5th spot with 55.4.
Please run GLM-5.3 and GLM-5.3-Flash. I would love to see how they do. On the smaller end of things, Qwen3.8-27B and Ling-3.0-Flash would also be interesting.
In the benchmark, have you considered instructing the models to build their own SPICE simulations to test their work? Simply asking them to write and run simulations could improve performance, even without telling them what to simulate.
We run each model multiple times against each challenge and take the average score. We include the variance below the score in the leaderboard.
GPT 5.5: 42.3±10.1
GPT 5.6 sol: 39.4±8.7
We were also surprised by the low sol score but it seems consistent with our experience in using it in the field in atopile as agent in our harness.
In general OpenAI models didn't do too well on electronics, which seems to change now with GPT-6 Astra. Results are in soon!
We spent a lot time evaluating which model is the best to use in our atopile agent harness and thought the benchmark and results are interesting enough to share.
Evaluating a model for specific use-cases like this that are bit more broad scope than a lot of typical microbenchmarks turned out to be quite the challenge.
Determining deterministically what a "good" electrical design is non-trivial and most electrical-engineers rely on good ol' intuition and decade long experience, so we tried to formalize it.
The only reason it was somewhat possible within a reasonable amount of effort is because atopile provides most of the complicated infrastructure for the benchmark: constraint solver, simulation, code-first electronics modeling, erc & drc checks, high level models of passive electronics components etc
They're 60 years old. The amount of training data on them is endless. Books, textbooks, videos, blog posts. The problem is when you want you do something that doesn't have 60 years of freely available documentation of their functions and applications
Like software, there's going to be a lot of pressure to use well documented tools within the model's training set. Innovation on the outputs may increase, but infrastructure and tooling will slow down.
If I'm making a PCB and I see anything older than 20 years, even glue logic, I'm very suspicious. Last time that happened (inherited design) the FETs didn't saturate and the LDO was just a DO... If the tool wants 7400 series logic, I'm not using the tool. None of my work is >= 5v signaling
I'm having it help design a 68k computer similar in spirit to the original Mac (the spirit being a tightly coupled video subsystem that time-shares the CPU bus), but updated with more modern peripherals, like PS/2 and SD cards. It's got the design more or less done, but the routing will be a nightmare. I'm not ready to just gamble on it having gotten everything right, so I will be doing a thorough design review myself and re-deriving all the timing analysis.
It's probably good at simple stuff. When you get problems like temperature dependent glitches, you need the engineering experience it doesn't give you (and an LA).
Love what samuel and his team are building over in the Netherlands!
Always thought it would be fun if there was a more beginner friendly version of atopile [1].
Cool! Looks like a company that grew out of §3.3.4 of SICP. Hardware oriented NixOS and GUIX users should be very interested in this: declarative PCB designs.
Sourcing parts has been a huge motivation for this. We are still pretty jarred by the supply chain crisis a few years ago. Having the ability to formally verify that an alternative part fulfills the original design constraints is huge.
Not sure whether you played with llm datasheet extraction lately, but they are working their way up there. Even started reasoning about curves and footnotes.
Where do you think is the biggest pain point: part discovery, datasheet verification or substitute determination?
Really excited about constraint solvers making a comeback! Especially after seeing Z3 getting a mention in anthropics fermat post.
EEbench is using atopile's internal constraint solver for engineering parameters (think operating temperature, voltage ranges, stacked tolerances etc).
