Firefly: lighting the path to a private supercluster

High-Flyer launched Firefly-1 (1,100 GPUs, ~200M yuan) then Firefly-2 (~10,000 NVIDIA A100s, over 1B yuan) while most quant funds were still renting cloud compute. Those A100s would later appear in DeepSeek V2 and V3 training logs — the firefly that lit an open-source generational leap.

While most quantitative funds were still renting cloud compute, High-Flyer launched Firefly-1: 1,100 GPUs, an investment of nearly 200 million yuan. It wasn't enough. Firefly-2 came online soon after — roughly 10,000 NVIDIA A100s, more than 1 billion yuan in capital. This is not a budget any CTO signs lightly: maintaining a ten-thousand-card cluster means a bottomless pit of cost, power, and cooling. But Liang Wenfeng saw that the only way to iterate trading models faster wasn't on someone else's cloud — it was in his own basement. Those A100s would later appear in DeepSeek V2 and V3 training logs, the firefly that ignited an open-source generational leap.