PCEval
LLM benchmark for physical computing: logical circuit generation, breadboard circuit generation, and code-hardware compatibility, evaluated automatically in simulation.
Summary rewritten from the vendor site because the catalog version did not match it.
What it does and how it connects
PCEval (Physical Computing Evaluation) is a benchmark for evaluating large language models on physical computing, where software must interact with and control physical hardware. It assesses LLMs in generating circuits and producing compatible code across varying levels of project complexity, without requiring human assessment.
The framework covers both the logical and physical aspects of projects: logical circuit design and code generation on one side, and physical breadboard layout creation on the other, all inside a simulation environment. The paper reports comprehensive testing of 13 leading models.
The findings show models perform well in code generation and logical circuit design but struggle significantly with physical breadboard layout creation, particularly in managing proper pin connections and avoiding circuit errors. The paper positions PCEval as a foundation for tools that support physical computing education.
Alternatives
Compare side by side- EmbedEval
EmbedEval tests implicit embedded-firmware knowledge with 267 cases, while PCEval tests physical computing across logical circuits, breadboards, and code.
- EmbedBench
EmbedBench tests embedded development with 126 cases across 3 hardware platforms, while PCEval tests physical computing in simulation.
- Embedded-LLM study (MDPI)
The MDPI study evaluates 27 models on 8 ESP32 IoT scenarios by expert review, while PCEval evaluates physical computing automatically in simulation.
- llm-firmware-benchmark
llm-firmware-benchmark is a Node harness for firmware coding tasks with deterministic fixtures, while PCEval tests physical computing in simulation.
- MMCircuitEval
MMCircuitEval tests circuit knowledge across EDA stages with 3,614 Q and A pairs, while PCEval tests physical computing with circuits and code.
Sources
Not verified
- Builder: the paper names three authors; no builder organization was verified in the sources read
- License: no benchmark or code license was stated in the sources read
- Pricing: none stated
- Real user voices (no real linked post read for this page)
- Related Error Index entries (no matching entry verified)
- A public code repository or dataset (none was stated on the paper page read)
Last verified November 6, 2026. Listings are informational. The evidence score measures public, verifiable evidence and is not an endorsement or a compatibility claim.