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nile-academy/qwen3.5-4b-gguf overview

qwen3.5 4b gguf Consumer supplied Wekala model library assets derived from the attributed official publisher. Models and this repository are distributed separa…

ggufwekalatext-generationbase_model:Qwen/Qwen3.5-4Bbase_model:quantized:Qwen/Qwen3.5-4Blicense:apache-2.0endpoints_compatibleregion:usconversational

Runs locally from ~2.59 GB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

Downloads
173
Likes
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Pipeline
text-generation

Repository Files & Downloads

2 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
Qwen3.5-4B-Q4_K_M.ggufGGUFQ4_K_M2.59 GBDownload
Qwen3.5-4B-Q8_0-llamacpp-4413a19.ggufGGUFQ8_04.29 GBDownload

Model Details

Model IDnile-academy/qwen3.5-4b-gguf
Authornile-academy
Pipelinetext-generation
Licenseapache-2.0
Base modelQwen/Qwen3.5-4B
Last modified2026-10-19T22:50:01.000Z

Model README

---

license: apache-2.0

base_model:

  • Qwen/Qwen3.5-4B

base_model_relation: quantized

library_name: gguf

pipeline_tag: text-generation

tags:

  • wekala
  • gguf

---

qwen3.5-4b-gguf

Consumer-supplied Wekala model-library assets derived from the attributed official publisher. Models and this repository are distributed separately from the Wekala SDK.

Origin and licence

| Field | Value |

| --- | --- |

| Original developer | Qwen Team, Alibaba Cloud |

| Original model | Qwen/Qwen3.5-4B |

| Pinned source revision | 851bf6e806efd8d0a36b00ddf55e13ccb7b8cd0a |

| Original publication | 2026-03-02 (day) |

| Date evidence | Publisher source |

| Licence | apache-2.0; preserved in LICENSE |

| Full source parameters | 4,659,865,088 (includes embeddings and source modalities) |

| Nile Academy role | Official artifact mirror or explicitly recorded format conversion; no additional training |

Original publisher cards and available notices are preserved in provenance/. The original model licence governs the weights; this repository grants no rights to the Wekala SDK.

Files and quantization

Q8_0 is the higher-precision comparison; Q6_K/Q5_K_M trade memory for precision; Q4_K_M needs paired task evaluation. No general quality-loss or 8GB-fit qualification yet.

| File | Quantization | Size (GB) | Origin |

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

| Qwen3.5-4B-Q8_0-llamacpp-4413a19.gguf | Q8_0 | 4.611 | existing Nile conversion; original lineage retained |

Exact file SHA-256 values, upstream paths/revisions and conversion receipts are recorded in model-metadata.json.

Published benchmarks

Publisher-reported source-model scores follow. They are not Wekala measurements of these quantized files. Harness, precision, reasoning settings and task versions differ; do not treat them as a normalized cross-model ranking.

| Benchmark | Score (%) | Mode / settings |

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

| MMLU-Pro | 79.1 | publisher-default; Publisher card protocol; cross-model scores are not normalized. |

| IFEval | 89.8 | publisher-default; Publisher card protocol; cross-model scores are not normalized. |

| BFCL-V4 | 50.3 | publisher-default; Publisher card protocol; cross-model scores are not normalized. |

Exact source card.

Qualification and use

Existing Windows development routes have separate readiness observations. Broad quality, sustained device fit, mobile/browser and owner acceptance remain separate.

Wekala broad quantization-quality qualification: not qualified. No general “no significant quality loss” claim is made. Official QAT or publisher comparisons are attributed separately. Before recommendation, use paired reference/variant evaluation across instruction, knowledge, math, multilingual/Arabic and tool tasks under the registered Wekala campaign.

Device fit is separate: weight size excludes context state, scratch buffers and driver headroom. CPU and CUDA are execution backends for the same weight file, not separate models. Mobile/browser and sustained 8GB-VRAM operation require their own measured profiles.

Models can produce incorrect or unsafe outputs. Tool calls are proposals subject to the consuming application’s permissions and controller admission.

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