Head to Head

unsloth/Qwen3.6-35B-A3B-GGUF vs HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive

Pricing, experience, and what the community actually says.

★ Our Pick

unsloth/Qwen3.6-35B-A3B-GGUF

unsloth/Qwen3.6-35B-A3B-GGUF

Starting at

0

Refund

N/A (Open-source model)

Try Free →
HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive

HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive

Starting at

0.00

Refund

N/A (Open-weight model)

Try Free →

Our Take

unsloth/Qwen3.6-35B-A3B-GGUFunsloth/Qwen3.6-35B-A3B-GGUF

“Yes, for developers and researchers seeking a capable, locally runnable LLM with a permissive Apache 2.0 license and low VRAM requirements.”

A highly efficient, open-weight MoE model that delivers strong coding and tool-calling capabilities while running on consumer hardware via GGUF quantization.

HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-AggressiveHauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive

“Yes, for developers and researchers who require an open-weight, uncensored MoE model with extensive quantization options and strong reasoning capabilities.”

A highly capable, unrestricted variant of the Qwen3.6-35B-A3B architecture, optimized for local deployment and specialized workflows requiring unfiltered outputs.

Pros & Cons

unsloth/Qwen3.6-35B-A3B-GGUF

✓Runs efficiently on consumer hardware (18-20GB VRAM at 4-bit)
✓Permissive Apache 2.0 license
✓Strong tool-calling and coding performance
✓Extensive framework compatibility
✓Free to download and modify
✗Requires technical setup for local deployment
✗Full-precision version demands enterprise GPUs
✗Incremental improvements over Qwen 3.5
✗Lower quantization levels may slightly impact output nuance
✗No official enterprise support tier

HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive

✓Completely removes safety refusal filters
✓Wide range of lossless GGUF quantizations for flexible hardware deployment
✓Strong coding and reasoning capabilities for its size
✓Native multimodal and long-context support
✓Free to download and self-host
✗Requires substantial VRAM for higher precision formats
✗Lacks built-in content moderation, requiring external safeguards
✗No official vendor support or SLA
✗Aggressive variant may produce unverified or harmful outputs without careful prompting

Full Breakdown

Category
unsloth/Qwen3.6-35B-A3B-GGUFunsloth/Qwen3.6-35B-A3B-GGUF
HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-AggressiveHauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive

Overall Rating

★8.5 / 5
8.2 / 5

Starting Price

0
0.00

Learning Curve

Moderate. Users need basic knowledge of GGUF formats, inference servers, and prompt configuration for optimal results.
Moderate; requires familiarity with local LLM inference tools like LM Studio, Ollama, or vLLM.

Best Suited For

Developers, AI researchers, and hobbyists running local inference, fine-tuning, or building agentic workflows on consumer GPUs or Apple Silicon.
Local AI deployment, uncensored content generation, agentic coding workflows, and long-context reasoning tasks.

Support Quality

Community-driven via Hugging Face discussions, GitHub issues, and Unsloth documentation. No dedicated enterprise support for the open-weight model.
Community-driven support via Hugging Face discussions and Discord. No official enterprise SLA.

Hidden Costs

Hardware costs for local deployment; cloud compute fees if using hosted inference or Unsloth Pro.
Compute costs for local hosting (GPU hardware, electricity) or cloud inference fees if deployed via third-party providers.

Refund Policy

N/A (Open-source model)
N/A (Open-weight model)

Platforms

Linux, macOS (Apple Silicon), Windows (via WSL/llama.cpp), Cloud GPU instances
Linux, macOS, Windows, Cloud GPU Instances

Features

Watermark on Free Plan

✗ No
✗ No

Mobile App

✗ No
✗ No

API Access

✓ Yes
✓ Yes
unsloth/Qwen3.6-35B-A3B-GGUF Review →Try Free →
HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive Review →Try Free →