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rasyosef/gemma-4-E4B-it-dspark-GGUF overview

gemma 4 E4B it dspark GGUF GGUF build of rasyosef/gemma 4 E4B it dspark https://huggingface.co/rasyosef/gemma 4 E4B it dspark for llama.cpp DSpark speculative …

llama.cppggufspeculative-decodingdsparkgemma-4draft-modeltext-generationbase_model:rasyosef/gemma-4-E4B-it-dsparkbase_model:quantized:rasyosef/gemma-4-E4B-it-dsparklicense:apache-2.0endpoints_compatibleregion:usconversational

Runs locally from ~569.2 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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text-generation
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Repository Files & Downloads

3 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
gemma-4-E4B-it-dspark-BF16.ggufGGUFBF161.03 GBDownload
gemma-4-E4B-it-dspark-F16.ggufGGUFF161.03 GBDownload
gemma-4-E4B-it-dspark-Q8_0.ggufGGUFQ8_0569.2 MBDownload

Model Details

Model IDrasyosef/gemma-4-E4B-it-dspark-GGUF
Authorrasyosef
Pipelinetext-generation
Licenseapache-2.0
Base modelrasyosef/gemma-4-E4B-it-dspark
Last modified2026-10-19T15:54:13.000Z

Model README

---

library_name: llama.cpp

base_model: rasyosef/gemma-4-E4B-it-dspark

base_model_relation: quantized

license: apache-2.0

pipeline_tag: text-generation

tags:

  • speculative-decoding
  • dspark
  • gemma-4
  • draft-model
  • gguf

---

gemma-4-E4B-it-dspark-GGUF

GGUF build of rasyosef/gemma-4-E4B-it-dspark for llama.cpp (DSpark speculative decoding is in mainline, ggml-org/llama.cpp #25173).

This is a standalone draft sidecar: it carries only the drafter (4 attention layers, rank-256 Markov head, confidence head, block size 8, 32,000-token draft vocabulary). Token embeddings and the LM head are shared from the target model at load time, so it must be paired with a gemma-4-E4B-it GGUF target file, for example one from unsloth/gemma-4-E4B-it-GGUF.

📦 Files

| file | quant | size | notes |

|---|---|---:|---|

| gemma-4-E4B-it-dspark-BF16.gguf | BF16 | 1.11 GB | native training precision, recommended when memory allows |

| gemma-4-E4B-it-dspark-F16.gguf | F16 | 1.11 GB | same size as BF16, for backends without good BF16 support |

| gemma-4-E4B-it-dspark-Q8_0.gguf | Q8_0 | 597 MB | smallest file, for tighter memory budgets |

Choose the draft quant by memory budget. The target model quant is the main speed/quality lever and is independent of this file.

🏃 How to run (llama.cpp)

llama-server -hf unsloth/gemma-4-E4B-it-GGUF:Q8_0 \
  -hfd rasyosef/gemma-4-E4B-it-dspark-GGUF:Q8_0 \
  --spec-type draft-dspark --spec-draft-n-max 8 --spec-draft-n-min 0 \
  -fa on -ngl 99

The block size is read from the sidecar metadata (n-max is clamped to it). Speculative decoding is exact: the target verifies every proposed token, so greedy output equals the target alone; per-response timings report draft_n / draft_n_accepted.

Other models in the DSpark GGUF family:

| Draft (GGUF) | Target |

|---|---|

| Llama-3.2-1B-Instruct-DSpark-GGUF | Llama-3.2-1B-Instruct |

| Llama-3.2-3B-Instruct-DSpark-GGUF | Llama-3.2-3B-Instruct |

| Qwen3-1.7B-DSpark-GGUF | Qwen3-1.7B |

| Qwen3.5-2B-DSpark-GGUF | Qwen3.5-2B |

| gemma-4-E2B-it-dspark-GGUF | gemma-4-E2B-it |

| gemma-4-E4B-it-dspark-GGUF | gemma-4-E4B-it |

| Phi-4-mini-instruct-DSpark-GGUF | Phi-4-mini-instruct |

📊 Acceptance and benchmarks

See rasyosef/gemma-4-E4B-it-dspark for acceptance-length metrics and training details.

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