TokForge

• Website: https://tokforge.ai
• Discord: https://discord.gg/Acv3CBtfVm
• Google Play: https://play.google.com/store/apps/details?id=dev.tokforge
• iOS TestFlight: https://testflight.apple.com/join/jnufjzRr

Runs on-device in the TokForge app.

Qwen3.5-13B-Deckard-Heretic-Uncensored-Thinking-MNN

Pre-converted Qwen3.5-13B-Deckard-Heretic-Uncensored-Thinking in MNN format for on-device inference with TokForge.

Original model by DavidAU — converted to MNN Q4 for mobile deployment.

Model Details

Architecture	Qwen3.5 (hybrid attention: full + LinearAttention, 48 layers)
Parameters	13B (4-bit quantized)
Format	MNN (Alibaba Mobile Neural Network)
Quantization	W4A16 (4-bit weights, block size 128)
Vocab	248,320 tokens
Source	DavidAU/Qwen3.5-13B-Deckard-Heretic-Uncensored-Thinking

Description

Deckard Heretic by DavidAU — a 13B Qwen3.5 model with thinking/reasoning capability and uncensored output. Named after the Blade Runner protagonist, this model excels at complex reasoning tasks while remaining uncensored. Supports <think> tags for chain-of-thought reasoning.

Files

File	Description
llm.mnn	Model computation graph
llm.mnn.weight	Quantized weight data (Q4, block=128)
llm_config.json	Model config with Jinja chat template
tokenizer.txt	Tokenizer vocabulary
config.json	MNN runtime config

Usage with TokForge

This model is optimized for TokForge — a free Android app for private, on-device LLM inference.

1. Download TokForge from the Play Store
2. Open the app → Models → Download this model
3. Start chatting — runs 100% locally, no internet required

Recommended Settings

Setting	Value
Backend	OpenCL (Qualcomm) / Vulkan (MediaTek) / CPU (fallback)
Precision	Low
Threads	4
Thinking	Off (or On for thinking-capable models)

Speculative Decoding

Speculative decoding is not recommended for this model. In our testing, draft pairing did not deliver reliable speedups on Qwen3.5 targets.

Performance

Actual speed varies by device, thermal state, and generation length. Typical ranges for this model size:

Device	SoC	Backend	tok/s
RedMagic 11 Pro	SM8850 (Snapdragon 8 Elite 2)	CPU	14.1 tok/s

Attribution

This is an MNN conversion of Qwen3.5-13B-Deckard-Heretic-Uncensored-Thinking by DavidAU. All credit for the model architecture, training, and fine-tuning goes to the original author(s). This conversion only changes the runtime format for mobile deployment.

Limitations

• Intended for TokForge / MNN on-device inference on Android
• This is a runtime bundle, not a standard Transformers training checkpoint
• Quantization (Q4) may slightly reduce quality compared to the full-precision original
• Abliterated/uncensored models have had safety filters removed — use responsibly

Community

• Website: tokforge.ai
• Discord: Join our Discord
• GitHub: TokForge on GitHub

Export Details

Converted using MNN's llmexport pipeline:

python llmexport.py --path DavidAU/Qwen3.5-13B-Deckard-Heretic-Uncensored-Thinking --export mnn --quant_bit 4 --quant_block 128