REDDIT · REDDIT// 3h agoNEWS

llama.cpp lines up MTP support

This Reddit post says Multi-Token Prediction support is about to land in llama.cpp and lists the model families that appear to support it, including DeepSeekv3 OG, DeepSeekv3.2/4, Qwen3.5, GLM4.5+, MiniMax2.5+, Step3.5Flash, and Mimo v2+. The poster notes that, until native MTP weights are available, users need to pull Hugging Face weights and convert them to GGUF, and they plan to test Qwen3.5-122B or GLM4.5-Air first.

// ANALYSIS

Hot take: this is less a flashy launch than an infrastructure unlock. The real value is not just “faster decoding,” but making MTP a practical option for the local-model crowd once the weights and conversion path are stable.

–The post lines up with llama.cpp’s draft MTP support PR and frames MTP as a compatibility milestone for local inference, not just a research concept. Source context: https://github.com/ggml-org/llama.cpp/pull/22673 and https://www.reddit.com/r/LocalLLaMA/comments/1t46o09/as_mtp_prepares_to_land_in_llamacpp_models_that/
–The biggest bottleneck is operational: people still need usable HF checkpoints and a clean GGUF conversion workflow before this becomes routine.
–The model list is already a moving target; commenters in the thread are debating whether specific Qwen and MiniMax variants actually support MTP, which suggests the ecosystem is still settling.
–If the speedups hold in practice, this is the kind of feature that can meaningfully change which local models people choose to run.

// TAGS

llama-cppmtpmulti-token-predictionlocal-firstquantizationqwendeepseekglmminimax

DISCOVERED

3h ago

2026-05-05

PUBLISHED

6h ago

2026-05-05

RELEVANCE

8/ 10

AUTHOR

segmond