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claymorecrystal/Qwen3.6-35B-A3B-uncensored-heretic-APEX-GGUF overview

< apex banner v2 <div style="background color: f59e0b; color: white; padding: 20px; border radius: 10px; text align: center; margin: 20px 0;" <h2 style="color:…

ggufquantizedapexmoemixture-of-expertsqwen3vlmvisionuncensoredhereticbase_model:llmfan46/Qwen3.6-35B-A3B-uncensored-hereticbase_model:quantized:llmfan46/Qwen3.6-35B-A3B-uncensored-hereticlicense:apache-2.0endpoints_compatibleregion:usconversational

Runs locally from ~861.0 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Repository Files & Downloads

8 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
Qwen3.6-35B-A3B-uncensored-heretic-APEX-Balanced.ggufGGUFGGUF23.87 GBDownload
Qwen3.6-35B-A3B-uncensored-heretic-APEX-Compact.ggufGGUFGGUF16.11 GBDownload
Qwen3.6-35B-A3B-uncensored-heretic-APEX-I-Balanced.ggufGGUFGGUF23.87 GBDownload
Qwen3.6-35B-A3B-uncensored-heretic-APEX-I-Compact.ggufGGUFGGUF16.11 GBDownload
Qwen3.6-35B-A3B-uncensored-heretic-APEX-I-Mini.ggufGGUFGGUF13.33 GBDownload
Qwen3.6-35B-A3B-uncensored-heretic-APEX-I-Quality.ggufGGUFGGUF21.25 GBDownload
Qwen3.6-35B-A3B-uncensored-heretic-APEX-Quality.ggufGGUFGGUF21.25 GBDownload
mmproj.ggufGGUFGGUF861.0 MBDownload

Model Details

Model IDclaymorecrystal/Qwen3.6-35B-A3B-uncensored-heretic-APEX-GGUF
Authorclaymorecrystal
Pipeline
Licenseapache-2.0
Base modelllmfan46/Qwen3.6-35B-A3B-uncensored-heretic
Last modified2026-06-20T12:39:01.000Z

Model README

---

license: apache-2.0

base_model: llmfan46/Qwen3.6-35B-A3B-uncensored-heretic

tags:

- gguf

- quantized

- apex

- moe

- mixture-of-experts

- qwen3

- vlm

- vision

- uncensored

- heretic

---

<!-- apex-banner-v2 -->

<div style="background-color: #f59e0b; color: white; padding: 20px; border-radius: 10px; text-align: center; margin: 20px 0;">

<h2 style="color: white; margin: 0 0 10px 0;">⚡ Each donation = another big MoE quantized</h2>

<p style="font-size: 18px; margin: 0 0 15px 0;">I host <b>25+ free APEX MoE quantizations</b> as independent research. My only local hardware is an <b>NVIDIA DGX Spark</b> (122 GB unified memory) — enough for ~30-50B-class MoEs, but <b>bigger ones (200B+) require rented compute</b> on H100/H200/Blackwell, typically $20-100 per quant.<br>If APEX quants are useful to you, your support directly funds those bigger runs.</p>

<p style="font-size: 20px; margin: 0;">

<a href="https://www.patreon.com/cw/mudler" style="color: white; text-decoration: underline;">🎉 Patreon (Monthly)</a> &nbsp;|&nbsp;

<a href="https://www.buymeacoffee.com/mudler" style="color: white; text-decoration: underline;">☕ Buy Me a Coffee</a> &nbsp;|&nbsp;

<a href="https://github.com/sponsors/mudler" style="color: white; text-decoration: underline;">⭐ GitHub Sponsors</a>

</p>

<p style="font-size: 14px; margin: 10px 0 0 0; opacity: 0.9;">💚 Big thanks to Hugging Face for generously donating additional storage — much appreciated.</p>

</div>

Qwen3.6 35B-A3B Uncensored Heretic APEX GGUF

APEX (Adaptive Precision for EXpert Models) quantizations of llmfan46/Qwen3.6-35B-A3B-uncensored-heretic.

Brought to you by the LocalAI team | APEX Project | Technical Report

Available Files

| File | Profile | Size | Best For |

|------|---------|------|----------|

| Qwen3.6-35B-A3B-uncensored-heretic-APEX-I-Balanced.gguf | I-Balanced | 24 GB | Best overall quality/size ratio |

| Qwen3.6-35B-A3B-uncensored-heretic-APEX-Balanced.gguf | Balanced | 24 GB | General purpose |

| Qwen3.6-35B-A3B-uncensored-heretic-APEX-I-Quality.gguf | I-Quality | 22 GB | Highest quality with imatrix |

| Qwen3.6-35B-A3B-uncensored-heretic-APEX-Quality.gguf | Quality | 22 GB | Highest quality standard |

| Qwen3.6-35B-A3B-uncensored-heretic-APEX-I-Compact.gguf | I-Compact | 17 GB | Consumer GPUs, best quality/size |

| Qwen3.6-35B-A3B-uncensored-heretic-APEX-Compact.gguf | Compact | 17 GB | Consumer GPUs |

| Qwen3.6-35B-A3B-uncensored-heretic-APEX-I-Mini.gguf | I-Mini | 14 GB | Smallest viable, fastest inference |

| mmproj.gguf | Vision projector | ~1 GB | Required for image understanding |

What is APEX?

APEX is a quantization strategy for Mixture-of-Experts (MoE) models. It classifies tensors by role (routed expert, shared expert, attention) and applies a layer-wise precision gradient — edge layers get higher precision, middle layers get more aggressive compression. I-variants use diverse imatrix calibration (chat, code, reasoning, tool-calling, agentic traces, Wikipedia).

The key insight: in MoE models, expert FFN tensors make up the bulk of model weight but only ~8/256 experts activate per token. APEX compresses middle-layer experts more aggressively while preserving edge layers (first/last 5) and keeping attention, SSM/Mamba, and shared expert tensors at higher precision.

See the APEX project for full details, technical report, and scripts.

Architecture

  • Model: Qwen3.6 35B-A3B Uncensored Heretic (uncensored fine-tune)
  • Base: Qwen 3.6 35B-A3B
  • Layers: 40
  • Experts: 256 routed + shared (8 active per token)
  • Total Parameters: ~35B
  • Active Parameters: ~3B per token
  • Attention: Hybrid (full attention every 4th layer, linear/Mamba otherwise)
  • Vision: Built-in vision encoder (mmproj included)
  • APEX Config: 5+5 symmetric edge gradient across 40 layers
  • Calibration: v1.3 diverse dataset (chat, code, reasoning, multilingual, tool-calling, Wikipedia)

Run with LocalAI

local-ai run mudler/Qwen3.6-35B-A3B-uncensored-heretic-APEX-GGUF@Qwen3.6-35B-A3B-uncensored-heretic-APEX-I-Balanced.gguf

Credits

Run claymorecrystal/Qwen3.6-35B-A3B-uncensored-heretic-APEX-GGUF with guIDE

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