A high-throughput facility in Menlo Park developed a specialized artificial intelligence that outperforms general frontier systems in the analysis of semiconductor materials. Periodic Labs calls the tool Neon, a 1 trillion parameter open-source LLM trained via mid-training and reinforcement learning. The model used 1,300 H200 GPUs and months of wet lab data to surpass GPT-6 Astra and Fable on benchmarks for superconductors and magnets.

The laboratory infrastructure reached 4.1x training throughput over a Megatron baseline and 2.5x faster decoding with cluster utilization above 95%. This architecture creates a cycle where AI manages lab operations and learns from the resulting data to inform future experiments. Periodic Labs contributes its technical improvements to open-source projects including Megatron-LM, SGLang and Miles.