Not always the latest, greatest, most hyped solutions deliver the best business outcomes.
Often, it is hard to measure the actual impact of the “new shiny thing” on the business. Everyone writes about the MTP (Multi-Token Prediction) and how it improves the LLM performance. I wanted to leverage it to boost my local AI development team.
My business case was the following:
I wanted to switch from Qwen3-Coder-Next-UD-Q4_K_XL to Qwen3.6-27B-MTP-UD-Q4_K_XL for local agentic coding. The Qwen3.6-27B is perceived to be “smarter” than Qwen3-Coder-Next, and I wanted to “upgrade” my local AI coders.
To validate the business outcome, I ran a several-hour benchmark on my local hardware. That was not a “generic stress test”; I measured the performance of various configurations in conditions closely simulating the “actual work environment” for my agents.
Unfortunately, the latest, greatest, most hyped solution does not move the needle for me. MTP did improve the Qwen3.6-27B performance, but the token-generation speed remained far behind Qwen3-Coder-Next.
My local AI team can iterate way faster using a tad less smart model. The potential quality gain does not compensate for the guaranteed speed reduction.
👉 Ensure to validate that tools provide the expected business outcome; do not trust the hype. Let me know if you could use my help in optimizing your business.