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Explore MTP (Multi-Token Prediction): 2x Faster Token Generation on AMD Strix Halo & Radeon 9700 AI Pro with 45,208 views, 1,268 likes, and 231 comments. Experience the impact of this video content that has captured audience attention.

#AMD_Partner. This video is sponsored by AMD. Join the AMD AI Developer Program for free cloud credits, expert access, and premium AI training - everything you need to build, optimize, and scale on AMD. Start building today: https://www.amd.com/en/developer/ai-dev-program.html ---------------------------------------------- Multi-Token Prediction (MTP) is one of the most practical ways to speed up local token generation. In this video, I break down how the MTP architecture works, how it acts as a built-in replacement for traditional speculative decoding without needing a separate draft model, and why it performs best on highly structured output like code generation. I walk through the recent integration of MTP into llama.cpp and show how to run it locally using Qwen 3.6. I also share benchmarks comparing performance on AMD Strix Halo and Radeon 9700 AI PRO GPUs. Timestamps: 00:00 | Introduction 01:03 | Prompt Processing / Token Generation 02:45 | Speculative Decoding 04:34 | Multi-Token Prediction (MTP) 06:44 | Where MTP Wotks Best 08:07 | Using MTP in llama.cpp 11:46 | Benchmarks 16:15 | Conclusion Links & Resources: Strix Halo Toolboxes & Tutorials: https://strix-halo-toolboxes.com Buy Me a Coffee: https://buymeacoffee.com/dcapitella llama.cpp MTP PR 22673: https://github.com/ggml-org/llama.cpp/pull/22673 MTP GGUFs (Qwen 3.6 27B): https://huggingface.co/ggml-org/Qwen3.6-27B-MTP-GGUF MTP GGUFs (Qwen 3.6 35B-A3B): https://huggingface.co/ggml-org/Qwen3.6-35B-A3B-MTP-GGUF Benchmark Script (mtp-bench.py): https://gist.github.com/am17an/228edfb84ed082aa88e3865d6fa27090 Reference Papers & Theory: Speculative Decoding Paper (Leviathan, Kalman, Matias - Google, 2023): https://arxiv.org/abs/2211.17192 Multi-Token Prediction Paper (Gloeckle et al. - Meta, 2024): https://arxiv.org/abs/2404.19737 DeepSeek-V3 Technical Report: https://arxiv.org/abs/2412.19437 Sebastian Raschka MTP Architecture Gallery: https://sebastianraschka.com/llm-architecture-gallery/mtp/ Community Explanations: Devsplainers - MTP Explanation: https://www.youtube.com/watch?v=aLq9DModnaw Hardware Used: - Platform 1: AMD Strix Halo Framework (Unified Memory) - Platform 2: 2x AMD Radeon AI PRO R9700 32GB (Discrete PCIe Setup)

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