Multi-Token Prediction for Qwen models lands in LLaMA.cpp with TurboQuant

Per a thread on r/LocalLLaMA, Multi-Token Prediction (MTP) support for Qwen models has landed in LLaMA.cpp alongside TurboQuant quantization.

MTP allows models to predict several tokens per forward pass, producing speculative decoding-style throughput gains without requiring a separate draft model. The implementation targets Qwen specifically and is available within the LLaMA.cpp ecosystem, which runs on consumer-grade hardware.

TurboQuant quantization ships alongside the MTP update, compressing model weights to reduce memory overhead and improve inference speed on devices without datacenter-class GPUs.

Together, the two features lower the compute cost of running Qwen locally — faster decoding at reduced VRAM requirements — without external serving infrastructure.

Builders deploying Qwen on edge devices or local rigs should evaluate whether updating to the MTP-enabled LLaMA.cpp build yields measurable latency reductions for their specific hardware and workload profiles.