DeepSeek V4 Pro costs 69× less than Fable 5 per task according to this chart. That gap may be one of the strongest arguments for open-weight AI. So how does DeepSeek make it so cheap? ↓ V4 Pro has 1.6 trillion parameters, but its MoE architecture activates only 49 billion per token. In other words: it gets the capacity of a gigantic model without running the entire model for every word. Then it cuts the inference bill further: • Sparse, compressed attention reduces long-context compute • FP4/FP8 precision lowers memory and bandwidth requirements • Prefix caching makes repeated inputs dramatically cheaper • Open weights let the entire ecosystem optimize deployment Cached API input is also priced roughly 120× lower than uncached input.