Is a Faster Model Actually Faster? Test the Whole Job — Morgan Suo, MiniMax

A faster model only helps if the finished job gets faster. Morgan Suo of MiniMax uses one real research task to test the changes inside the M3.1 Flash model: an analyst checking whether circuit-board suppliers are turning AI demand into cash. The changes are sparse attention on long inputs, a 4-bit KV cache, low-precision experts, speculative decoding, server load and reasoning budgets. Each one saves compute, and each can quietly cost accuracy or wait time. She then shows how to judge a model switch: check sources and calculations, count the full cost of a usable report, and make the result repeatable. Chapters: - 00:00 Intro - 01:44 The research job - 03:20 Profit vs. cash flow - 04:22 What changed inside the model - 05:09 Sparse attention on long inputs - 07:53 4-bit KV cache - 08:59 Low-precision experts - 10:20 Speculative decoding - 11:39 Throughput vs. wait time - 13:09 Reasoning budgets - 14:41 How to evaluate a model switch - 16:12 Recap Morgan Suo, MiniMax: https://www.minimax.io Join us in SF for the second annual AIE CODE summit: https://aie.codes our last flagship summit of 2026. Applications live now!