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matrixportalx/gemma-4-E4B-it-assistant-MTP-GGUF overview

Gemma 4 E4B — MTP assistant head · GGUF GGUF conversions of google/gemma 4 E4B it assistant , the Gemma 4 Multi Token Prediction MTP assistant head — architect…

ggufllama.cppgemma4mtpspeculative-decodingbase_model:google/gemma-4-E4B-it-assistantbase_model:quantized:google/gemma-4-E4B-it-assistantlicense:gemmaendpoints_compatibleregion:us

Runs locally from ~73.4 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Repository Files & Downloads

4 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
gemma-4-E4B-it-assistant-Q4_0.ggufGGUFQ4_073.4 MBDownload
gemma-4-E4B-it-assistant-Q6_K.ggufGGUFQ6_K76.1 MBDownload
gemma-4-E4B-it-assistant-Q8_0.ggufGGUFQ8_094.1 MBDownload
gemma-4-E4B-it-assistant-f16.ggufGGUFF16163.8 MBDownload

Model Details

Model IDmatrixportalx/gemma-4-E4B-it-assistant-MTP-GGUF
Authormatrixportalx
Pipeline
Licensegemma
Base modelgoogle/gemma-4-E4B-it-assistant
Last modified2026-07-19T22:18:34.000Z

Model README

---

license: gemma

base_model: google/gemma-4-E4B-it-assistant

tags:

- gguf

- llama.cpp

- gemma4

- mtp

- speculative-decoding

library_name: gguf

---

Gemma 4 E4B — MTP (assistant) head · GGUF

GGUF conversions of google/gemma-4-E4B-it-assistant, the Gemma 4

Multi-Token-Prediction (MTP) assistant head — architecture gemma4-assistant

in llama.cpp.

> These are not a standalone chat model. This is the small speculative /

> draft-mtp head (~76M parameters) that runs alongside a Gemma 4 E4B main

> model to accelerate generation via speculative decoding. Load it as the draft

> model, not as the primary model.

Files

| File | Type |

|------|------|

| gemma-4-E4B-it-assistant-f16.gguf | F16 |

| gemma-4-E4B-it-assistant-Q4_0.gguf | Q4_0 |

| gemma-4-E4B-it-assistant-Q6_K.gguf | Q6_K |

| gemma-4-E4B-it-assistant-Q8_0.gguf | Q8_0 |

All variants are converted from the original bf16 checkpoint with

llama.cpp (commit f955e39).

Choosing a quantization

Most of this head's weights live in the token-embedding tensor, so quantization

mainly shrinks the embedding:

  • F16 — highest draft acceptance rate; recommended when disk isn't a concern.
  • Q8_0 — near-F16 quality, ~half the size.
  • Q6_K — smaller still, minor acceptance loss.
  • Q4_0 — smallest; acceptance drops the most (the embedding is quantized to 4-bit).

Because the head is tiny to begin with, the size savings from lower bit-widths

are modest while acceptance decreases — F16 or Q8_0 are the practical picks.

Usage (llama.cpp speculative decoding)

Use this file as the draft/MTP head together with a Gemma 4 E4B main model in a

llama.cpp build that supports gemma4 MTP (draft-mtp) speculative decoding.

The head shares the KV cache with the target model. Typical speculative-decoding

settings: n_max (draft length) of 3 tends to give the best throughput;

higher values reduce acceptance and can end up slower than no speculation.

Base model & license

Derived from the gated model

google/gemma-4-E4B-it-assistant.

Distributed under the Gemma license;

you are responsible for complying with Google's Gemma Terms of Use.

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