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jglowa/Bielik-11B-v3.0-DFlash-GGUF overview

Bielik 11B v3.0 DFlash GGUF This repository provides GGUF files with F16 and Q8 0 quantization of Bielik 11B v3.0 DFlash https://huggingface.co/speakleash/Biel…

ggufdflashspeculative-decodingblock-diffusiondraft-modelefficiencybielikdiffusion-language-modeltext-generationmultilingualplensqbelbsbghrcsdaetfifreles

Runs locally from ~1.16 GB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

Downloads
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Pipeline
text-generation
Author

Repository Files & Downloads

4 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
Bielik-11B-v3.0-DFlash-F16.ggufGGUFF162.19 GBDownload
Bielik-11B-v3.0-DFlash-Q8_0.ggufGGUFQ8_01.16 GBDownload
beellama.cpp/Bielik-11B-v3.0-DFlash-F16.ggufGGUFF162.19 GBDownload
beellama.cpp/Bielik-11B-v3.0-DFlash-Q8_0.ggufGGUFQ8_01.16 GBDownload

Model Details

Model IDjglowa/Bielik-11B-v3.0-DFlash-GGUF
Authorjglowa
Pipelinetext-generation
Licenseapache-2.0
Base modelspeakleash/Bielik-11B-v3.0-DFlash
Last modified2026-07-03T09:52:29.000Z

Model README

---

license: apache-2.0

language:

  • multilingual
  • pl
  • en
  • sq
  • bel
  • bs
  • bg
  • hr
  • cs
  • da
  • et
  • fi
  • fr
  • el
  • es
  • is
  • lt
  • nl
  • de
  • 'no'
  • pt
  • ru
  • ro
  • sr
  • hbs
  • sv
  • sk
  • sl
  • tr
  • uk
  • hu
  • it
  • lv

pipeline_tag: text-generation

tags:

  • dflash
  • speculative-decoding
  • block-diffusion
  • draft-model
  • efficiency
  • bielik
  • diffusion-language-model

base_model:

  • speakleash/Bielik-11B-v3.0-DFlash

---

Bielik-11B-v3.0-DFlash-GGUF

This repository provides GGUF files with F16 and Q8_0 quantization of Bielik-11B-v3.0-DFlash model by SpeakLeash for use in llama.cpp/beellama.cpp.

Bielik-11B-v3.0-DFlash is a DFlash draft model designed for use with Bielik-11B-v3.0-Instruct.

Its development and training were supported by computational grant PLG/2026/019559 and carried out on the Helios supercomputer, providing access to the advanced infrastructure and computational resources required for large-scale machine learning workloads.

This is not a standalone language model. It is designed to be paired with the target model in a speculative decoding setup.

How to use

llama.cpp

Install llama.cpp and one of the GGUF files in the root directory, then run Bielik like this:

llama-cli -m Bielik-11B-v3.0-Instruct-Q8_0.gguf --spec-type draft-dflash --spec-draft-model Bielik-11B-v3.0-DFlash-Q8_0.gguf --spec-draft-ngl all --spec-draft-n-min 16 -fa on

beellama.cpp

Install beellama.cpp and one of the GGUF files in the beellama.cpp directory, then run Bielik like this:

llama-cli -m Bielik-11B-v3.0-Instruct-Q8_0.gguf --spec-type dflash --spec-draft-model Bielik-11B-v3.0-DFlash-Q8_0.gguf --spec-draft-ngl all --spec-draft-n-min 16 -fa on

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