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dev7a/DeepSeek-V4-Pro-DSpark-Drafter-GGUF
DeepSeek-V4-Pro-DSpark-Drafter-GGUF is a machine learning model from dev7a. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for gguf. The card lists the license as mit.
This repository contains two DSpark auxiliaries for DeepSeek V4 Pro. They are not standalone language models and do not include target-model weights.
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.gguf68.7 GB · 100%
From the Hugging Face model README
This repository contains two DSpark auxiliaries for DeepSeek V4 Pro. They are not standalone language models and do not include target-model weights.
| File | Routed experts | Dense projections | Bytes | SHA-256 |
|---|---|---|---|---|
DeepSeek-V4-Pro-DSpark-Drafter-MXFP4-Q8_0-dflash.gguf | MXFP4 | Q8_0 | 42,079,461,248 | 50b440862e90b86b14e90adab9c1d92aaaff4cf6ad7658b65232a78b87ffb0be |
DeepSeek-V4-Pro-DSpark-Drafter-Q2_K-Q8_0-dflash.gguf | Q2_K | Q8_0 | 26,621,353,856 | 9e53ffd4fc6bd298ad4d1428f7da1d88615b266294ef2f1f4f95b9ac1279169a |
Both 81-tensor GGUFs use the standardized llama.cpp
general.architecture=dflash schema. Use MXFP4 for higher routed-expert
fidelity when the complete launch fits. Use Q2_K when memory is tighter.
hf download dev7a/DeepSeek-V4-Pro-DSpark-Drafter-GGUF \
DeepSeek-V4-Pro-DSpark-Drafter-MXFP4-Q8_0-dflash.gguf
The source is deepseek-ai/DeepSeek-V4-Pro-DSpark revision
7c09739fd136abfb70a49ec334157f65f45b52cd. Only source shards 64 through 66
contain the complete auxiliary. Their sizes and SHA-256 values are pinned in
manifest/source.json.
The repository contains the deterministic converter, standardized dflash
rewriter, independent numeric verifier, tests, build manifests, payload
comparisons, and checksums. Both quantization recipes and both schema rewrites
were repeated and produced byte-identical results.
The standardized files carry the complete target tokenizer copied through the
official llama.cpp DeepSeek V4 DSpark converter at commit
15586e2d7165570fb3aa7c26e0d442e289ef69de, including
tokenizer.ggml.mask_token_id=128799. The Flash-compatible artifact produced by
the same builder passed a real llama.cpp draft-dspark decode with 120 draft
tokens generated, 38 accepted, and no invalid -1 token.
Reproduce either artifact on Linux AArch64 with Python 3.14:
uv venv --python 3.14.6 .venv
uv pip install --python .venv/bin/python \
--require-hashes --only-binary=:all: \
-r requirements-linux-aarch64-py314.lock
.venv/bin/python scripts/download_sources.py --destination sources
.venv/bin/python -m unittest discover -s tests -v
recipe=mxfp4-q8_0
.venv/bin/python scripts/reproduce.py \
--sources sources --recipe "$recipe" \
--manifest-dir manifest --repeat-check
.venv/bin/python scripts/dflash.py \
--sources sources --recipe "$recipe" \
--legacy-input DeepSeek-V4-Pro-DSpark-Drafter-MXFP4-Q8_0.gguf \
--target-tokenizer-gguf tokenizer.gguf \
--manifest-dir manifest --repeat-check
Use recipe=q2_k-q8_0 and the corresponding Q2_K legacy filename to reproduce
the compact variant.
Use these files only with a compatible DeepSeek V4 Pro target. The runtime must
support the standardized llama.cpp dflash GGUF schema, MXFP4, and Q2_K as
required by the selected file. Always validate the complete target and drafter
memory plan before acquisition.
This is a community conversion, not an official DeepSeek release. The
source-derived weights remain under DeepSeek's MIT license. Conversion code and
third-party notices are provided in LICENSE.code and
THIRD_PARTY_NOTICES.md.