Descriptions:
Fahd Mirza demonstrates how to enable Multi-Token Prediction (MTP) speculative decoding in LM Studio’s new beta release (version 0.4.14 or higher), achieving a 63% speed increase on Qwen3.6-27B with no degradation in output quality. The video builds on earlier coverage of MTP landing in mainline llama.cpp and shows how the feature has now been surfaced as a single UI toggle — accessible without touching a terminal.
MTP works by baking prediction heads directly into the model weights during training, eliminating the need for a separate draft model. The main head predicts the next token while additional MTP heads simultaneously predict tokens two and three positions ahead, all using the same hidden states. A single verifier forward pass then confirms all predictions, yielding multiple tokens at roughly the cost of one pass — same output, more throughput.
The demo runs on an Nvidia RTX 6000 with 48GB VRAM on Ubuntu, with a baseline measurement of approximately 20.24 tokens per second before enabling MTP. Side-by-side quality comparison is included to confirm output equivalence. The tutorial covers downloading LM Studio, selecting the correct Qwen3.6-27B GGUF quant from the official GGML source, loading the model without MTP first to establish a baseline, then toggling MTP on under advanced settings. A practical how-to for anyone running local LLMs who wants significantly more throughput from hardware they already own.
📺 Source: Fahd Mirza · Published May 20, 2026
🏷️ Format: Tutorial Demo
