Multi-Token Prediction Work Resumes for Qwen Flash Next in llama.cpp
Development on Multi-Token Prediction (MTP) support for Qwen Flash Next models in llama.cpp has resumed. Updated GGUF quants are now available on Hugging Face alongside an active pull request on GitHub. Integrating MTP support into llama.cpp enables faster inference speeds and improved generation capabilities for Qwen models running locally. This update allows open-source local AI users to test state-of-the-art decoding techniques on consumer hardware. The implementation is still marked as a work-in-progress and is tracked under GitHub PR #29761. Testing models can be downloaded from the `ggml-org/Qwen3.8-Flash-Next-GGUF` Hugging Face repository.
## BACKGROUND
Multi-Token Prediction (MTP) is an architecture pattern where an LLM predicts multiple future tokens simultaneously rather than autoregressively predicting just one, accelerating inference and speculative decoding. llama.cpp is a popular C/C++ execution engine that uses the GGUF file format to efficiently run quantized LLMs on local devices.