Head to Head

z-lab/Qwen3.6-35B-A3B-DFlash vs HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive

Pricing, experience, and what the community actually says.

z-lab/Qwen3.6-35B-A3B-DFlash

Starting at

Refund

Open-weight model; no refunds applicable.

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★ Our Pick

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

Starting at

0.00

Refund

N/A (Open-weight model)

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Our Take

z-lab/Qwen3.6-35B-A3B-DFlash

“Yes for developers and researchers with adequate GPU resources who prioritize open licensing, local deployment, and agentic coding workflows.”

A highly capable open-weight MoE model that delivers strong coding and reasoning performance with efficient inference, though it requires substantial local hardware and technical setup.

HauhauCS/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

z-lab/Qwen3.6-35B-A3B-DFlash

✓Strong coding and repository-level reasoning

✓Efficient MoE architecture reduces active compute

✓Thinking preservation improves iterative workflows

✓Permissive Apache 2.0 licensing

✓Compatible with major open-source inference frameworks

✗Requires ~24GB VRAM for full deployment

✗Setup and optimization require technical expertise

✗No official enterprise support or SLA

✗Raw inference speed depends heavily on backend configuration

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

z-lab/Qwen3.6-35B-A3B-DFlash

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

Overall Rating

4.3 / 5

★8.2 / 5

Starting Price

0.00

Learning Curve

Moderate to high; requires familiarity with LLM inference frameworks (vLLM, SGLang, Transformers) and hardware optimization.

Moderate; requires familiarity with local LLM inference tools like LM Studio, Ollama, or vLLM.

Best Suited For

Software engineers, AI researchers, and developers building local or self-hosted AI agents, code assistants, and long-context applications.

Local AI deployment, uncensored content generation, agentic coding workflows, and long-context reasoning tasks.

Support Quality

Community-driven support via Hugging Face discussions, GitHub issues, and developer forums. No official enterprise SLA.

Community-driven support via Hugging Face discussions and Discord. No official enterprise SLA.

Hidden Costs

Hardware requirements (24GB+ VRAM) and potential cloud GPU rental fees for inference hosting.

Compute costs for local hosting (GPU hardware, electricity) or cloud inference fees if deployed via third-party providers.

Refund Policy

Open-weight model; no refunds applicable.

N/A (Open-weight model)

Platforms

Linux, macOS, Windows, Cloud GPU Instances

Features

Watermark on Free Plan

✗ No

Mobile App

✗ No

API Access

✓ Yes

z-lab/Qwen3.6-35B-A3B-DFlash Review →Try Free →

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