quimmedes

Deepwen-3.6-bf16

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README

License: apache-2.0

What the model has

Advanced thinking (DeepSeek style) — the model reasons before it answers. Its thinking comes from two sources:
- Supervised reasoning training: 93.6% of its reasoning-focused training examples (103/110) carry a full reasoning chain as part of the target.
- Reasoning-effort control: a chat template ported from deepseek-ai/DeepSeek-V4-Flash-0731, with three effort levels — low (default), xhigh, and max ("Beyond maximum — exhaustive, relentless... do not stop reasoning until you have independently verified the solution from multiple angles").
Procedural 3D generation — explicit blockout gating before high-poly, conditional lightmap workflows, combinatorial validation, non-destructive pipelines.
Hard-surface shape language — stance/relational design, primary volume architecture, motif propagation, panel breakup.
Multi-skill asset workflows — Blender modifier-driven gear recipes, tooth profile generation, PBR game-prep, layered lighting legibility.

Format

safetensors, bfloat16 (26 shards, ~67 GB)
Base dtype: bf16; Mamba SSM tensors in f32
Includes the full model (no MTP layers stripped at this level)

Improvements over the base model

Table with columns: Capability, Improvement
Capability	Improvement
Procedural generation	`blockout_gate`: PARTIAL → PASS; `conditional_lightmap`: FAIL → PASS
Replay safety	base competence suite 6/6 intact (no regressions)
Shape / hard-surface	no catastrophic flips across held-out objects
Blender gear recipe	modifier_workflow, tooth_profile_generation, game_prep_uv_pbr, non_destructive_order
Lighting	layered lighting legibility (bounce and ambient)

Usage

Standard transformers / vLLM / SGLang loading:

python
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("quimmedes/Deepwen-3.6-bf16", torch_dtype="bfloat16")
tok = AutoTokenizer.from_pretrained("quimmedes/Deepwen-3.6-bf16")

To enable advanced thinking at maximum effort:

json
{
  "messages": [{"role": "user", "content": "..."}],
  "chat_template_kwargs": {"reasoning_effort": "max"}
}

Quantized versions

GGUF quantizations with MoQ (mixed) tensor types are published in:

quimmedes/Deepwen-3.6 — levels Q2.5 (IQ2_XXS), Q3, Q4.5, Q5, Q6, Q8, all without MTP (733 tensors), plus vision mmproj (BF16/F16).

Disclosures

Base model: Qwen/Qwen3.6-35B-A3B — Copyright © Alibaba Group / Qwen Team. All rights to the base model and its weights remain with the original authors.
The base model is released under the Apache License 2.0; this derivative inherits that license.
Qwen 3.6 is a copyrighted, trademarked model family of Alibaba. "Deepwen 3.6" is an independent fine-tuned derivative and is not affiliated with, endorsed by, or sponsored by Alibaba / Qwen. The "Qwen" name is used solely to identify the base model.
The embedded reasoning-effort prompts are adapted from the chat template of deepseek-ai/DeepSeek-V4-Flash-0731; DeepSeek remains the copyright holder of those prompt texts.
MoQ quantization method: "Mixture of Quantizations" proposed by Waleed Ahmad (https://huggingface.co/w-ahmad).
This model is provided as-is, without warranties of any kind, for research and local experimentation.

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Model Details

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Supported Functionality