# Gemma 4 E4B MTP drafter Multi-Token Prediction (MTP) drafter for `unsloth/gemma-4-E4B-it-GGUF`. It runs as a speculative draft model that shares the target's KV cache and speeds up text generation. Verified on a single B200 with the `gemma-4-E4B-it-Q4_K_M.gguf` target: 150 tok/s without MTP, 214 tok/s with MTP, 0.66 draft acceptance. MTP for E4B was added to llama.cpp on 2026-06-08 (PR ggml-org/llama.cpp#24282). You need a llama.cpp build from after that date. Older builds cannot load these (arch `gemma4-assistant`). Run E4B with `-fa off`. With flash attention on, the draft model currently aborts in the CUDA flash attention kernel. ## Files For `-hf` auto-discovery a Q8_0 drafter sits at the repo root as `mtp-gemma-4-E4B-it.gguf`. The same three precisions live in `MTP/`: - `gemma-4-E4B-it-Q8_0-MTP.gguf` (smallest, recommended; mirrored at the repo root as `mtp-gemma-4-E4B-it.gguf`) - `gemma-4-E4B-it-BF16-MTP.gguf` - `gemma-4-E4B-it-F16-MTP.gguf` ## Build llama.cpp ```bash git clone https://github.com/ggml-org/llama.cpp cd llama.cpp # CUDA build. Set the arch for your GPU: 89 (RTX 4090), 90 (H100), 100 (B200). cmake -B build -DGGML_CUDA=ON -DCMAKE_CUDA_ARCHITECTURES=90 cmake --build build --config Release -j --target llama-server ``` ## Run, the easy way A recent llama.cpp finds the drafter automatically from the root `mtp-` file, so `-hf` is all you need. No `--model-draft`. ```bash ./build/bin/llama-server \ -hf unsloth/gemma-4-E4B-it-GGUF:Q4_K_M \ --spec-type draft-mtp --spec-draft-n-max 4 \ -ngl 999 -fa off ``` If your build is too old to auto-discover the sibling, use the explicit form below. ## Run with an explicit drafter Use this to choose a precision or point at a local file. ```bash hf download unsloth/gemma-4-E4B-it-GGUF gemma-4-E4B-it-Q4_K_M.gguf --local-dir . hf download unsloth/gemma-4-E4B-it-GGUF MTP/gemma-4-E4B-it-Q8_0-MTP.gguf --local-dir . ./build/bin/llama-server \ -m gemma-4-E4B-it-Q4_K_M.gguf \ --model-draft MTP/gemma-4-E4B-it-Q8_0-MTP.gguf \ --spec-type draft-mtp --spec-draft-n-max 4 \ -ngl 999 -fa off ``` Multi GPU: add `--spec-draft-device CUDA0 -sm layer`. The drafter pairs with any quant of the E4B. Quantized KV cache works.