| Name | Size | Uploaded | Xet hash |
|---|---|---|---|
| README.md | 2.1 kB xet | 3e4751a3 | |
| gemma-4-E2B-it-BF16-MTP.gguf | 170 MB xet | 5f5d8370 | |
| gemma-4-E2B-it-F16-MTP.gguf | 170 MB xet | e1424d96 | |
| gemma-4-E2B-it-Q8_0-MTP.gguf | 97.8 MB xet | c5d152a8 |
Gemma 4 E2B MTP drafter
Multi-Token Prediction (MTP) drafter for unsloth/gemma-4-E2B-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-E2B-it-Q4_K_M.gguf target: 287 tok/s without MTP, 350 tok/s with MTP, 0.55 draft acceptance.
MTP for E2B 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).
Files
For -hf auto-discovery a Q8_0 drafter sits at the repo root as mtp-gemma-4-E2B-it.gguf. The same three precisions live in MTP/:
gemma-4-E2B-it-Q8_0-MTP.gguf(smallest, recommended; mirrored at the repo root asmtp-gemma-4-E2B-it.gguf)gemma-4-E2B-it-BF16-MTP.ggufgemma-4-E2B-it-F16-MTP.gguf
Build llama.cpp
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.
./build/bin/llama-server \
-hf unsloth/gemma-4-E2B-it-GGUF:Q4_K_M \
--spec-type draft-mtp --spec-draft-n-max 4 \
-ngl 999 -fa on
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.
hf download unsloth/gemma-4-E2B-it-GGUF gemma-4-E2B-it-Q4_K_M.gguf --local-dir .
hf download unsloth/gemma-4-E2B-it-GGUF MTP/gemma-4-E2B-it-Q8_0-MTP.gguf --local-dir .
./build/bin/llama-server \
-m gemma-4-E2B-it-Q4_K_M.gguf \
--model-draft MTP/gemma-4-E2B-it-Q8_0-MTP.gguf \
--spec-type draft-mtp --spec-draft-n-max 4 \
-ngl 999 -fa on
Multi GPU: add --spec-draft-device CUDA0 -sm layer. The drafter pairs with any quant of the E2B. Quantized KV cache works.
- Total size
- 80.8 GB
- Files
- 33
- Last updated
- Jun 24
- Pre-warmed CDN
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