Troubleshooting RAM/VRAM Allocation for MTP in llama.cpp
xornullvoid · reddit · 2026-07-30
A developer encountered a memory allocation issue while deploying a model with llama.cpp using MTP (Multi-Token Prediction) speculative decoding.
- Issue: System RAM usage keeps increasing even though there is more than 10GB of VRAM space left.
- Core Question: Does the MTP head load separately from the main model? Is it necessary to explicitly set the device for it in the arguments?
- Setup: The llama-server command is configured with --spec-type draft-mtp and related speculative decoding parameters.
More from Infra
- MIT-founded Atomarine Aims for Underwater Data Centers to Power AI — bosmeny · 2026-07-30
- AI Demand Far Outpaces Supply as Infrastructure Becomes the Bottleneck — NinaDSchick · 2026-07-30
- Open-source project runs 120B MoE models on smartphones at 6 tokens/s — dai_app · 2026-07-30
- How Open-Source Small Models Power Edge AI for Wildfire Detection in France — import_jmr · 2026-07-30
- Post-training pain points: messy parallel experiments, dependency hell, high GPU costs — Pitiful-Minute-2818 · 2026-07-30
- Nscale Acquires Anyscale to Own More of the AI Compute Stack — TechCrunch AI · 2026-07-30