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TeichAI/Qwen3.6-27B-Fable-5-Experimental-GGUF overview

Qwen 3.6 27B Claude Fable 5 Experimental <div style="border left: 4px solid D97706; background: rgba 217, 119, 6, 0.08 ; padding: 14px 16px; border radius: 8px…

ggufllama.cppunslothqwen3_5endataset:armand0e/claude-fable-5-claude-codebase_model:TeichAI/Qwen3.6-27B-Fable-5-Experimentalbase_model:quantized:TeichAI/Qwen3.6-27B-Fable-5-Experimentallicense:apache-2.0endpoints_compatibleregion:usconversational

Runs locally from ~884.6 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Repository Files & Downloads

11 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
Qwen3.6-27B-Fable-5-Distill.bf16.ggufGGUFGGUF50.90 GBDownload
Qwen3.6-27B-Fable-5-Distill.iq4_nl.ggufGGUFGGUF15.59 GBDownload
Qwen3.6-27B-Fable-5-Distill.q3_k_m.ggufGGUFGGUF13.18 GBDownload
Qwen3.6-27B-Fable-5-Distill.q3_k_s.ggufGGUFGGUF12.04 GBDownload
Qwen3.6-27B-Fable-5-Distill.q4_k_m.ggufGGUFGGUF16.20 GBDownload
Qwen3.6-27B-Fable-5-Distill.q5_k_m.ggufGGUFGGUF18.70 GBDownload
Qwen3.6-27B-Fable-5-Distill.q6_k.ggufGGUFGGUF21.36 GBDownload
Qwen3.6-27B-Fable-5-Distill.q8_0.ggufGGUFGGUF27.42 GBDownload
mmproj-BF16.ggufGGUFBF16888.0 MBDownload
mmproj-F16.ggufGGUFF16884.6 MBDownload
mmproj-F32.ggufGGUFF321.72 GBDownload

Model Details

Model IDTeichAI/Qwen3.6-27B-Fable-5-Experimental-GGUF
AuthorTeichAI
Pipeline
Licenseapache-2.0
Base modelTeichAI/Qwen3.6-27B-Fable-5-Experimental
Last modified2026-06-23T17:36:35.000Z

Model README

---

base_model: TeichAI/Qwen3.6-27B-Fable-5-Experimental

tags:

  • gguf
  • llama.cpp
  • unsloth
  • qwen3_5

license: apache-2.0

language:

  • en

datasets:

  • armand0e/claude-fable-5-claude-code

---

Qwen 3.6 27B - Claude Fable 5 (Experimental)

<div style="border-left: 4px solid #D97706; background: rgba(217, 119, 6, 0.08); padding: 14px 16px; border-radius: 8px; margin: 16px 0;">

<strong style="color: #D97706;">Update · 6/22/2026</strong><br>

GGUFs re-done with MTP built in.<br>

<strong>llama.cpp MTP args:</strong>

<code>--spec-type draft-mtp --spec-draft-n-max 3</code>

</div>

Heres Qwen3.6 slightly over-trained on a very small dataset of fable 5 traces.

Had to use aggressive settings for the style transfer here due to the data contraints. Overall the model seems to be a better planner now and better at 3D modeling in three.js, making small games, and ML engineering.

Either way give it a shot, it really does look, talk, and plan like fable... but like all fine-tunes it comes with it's limitations.

Hopefully we can get some more well rounded data from the rest of the community to a do a much less aggressive tune on a larger dataset.

Reasoning was left untouched

Benchmarks

!Benchmark Comparison

As always big thanks to @nightmedia for the speedy benchmarks.

                                 arc     arc/e	boolq
Qwen3.6-27B-Fable-5-Experimental 0.650	0.813	0.909
                     Qwen3.6-27B	0.637	0.798	0.911

Not really a benchmark but here's a procedurally generated duck that it zero-shotted lol (quant: q3_k_s)

!image

---

The data for this model was easily extracted, formatted, and masked for training with Teich <img src="https://cdn-avatars.huggingface.co/v1/production/uploads/6837935ac3b7ffe0d2559ce9/-AxyvV4wfUY8uo87kNKkK.png" width="20" height="20" style="display: inline-block; vertical-align: middle; margin: 0 3px;">

This model was trained 2x faster with Unsloth and Huggingface's TRL library.

<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>

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