【2026】Qwen3.6-35B Genesis Hermes GGUF Complete Guide: Running an Uncensored Multimodal MoE on Your Local PC

「I want to run the latest big AI models freely on my own PC」「But cloud costs money, and I worry about censorship…」

There's a model making waves in 2026: Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-V3-GGUF.

Based on Alibaba's Qwen3.6, it's polished into an "Uncensored" + "Hermes agent-specialized" + "GGUF format (runs on local PC)" model. It's also a multimodal (MoE) model that can read images.

This article explains the model's features and how to actually run it on your home PC, in a beginner-friendly way.

What You'll Learn

What Qwen3.6-35B Genesis Hermes is
Why "uncensored" is great
Specs needed to run it locally
Setup steps with llama.cpp / Ollama
Recommended quantization (lightweight running tips)
Related hardware

What Is Qwen3.6-35B Genesis Hermes?

In short: "a local-friendly, freer version of Alibaba's latest MoE model Qwen3.6."

3 Key Points

① Uncensored Normal public models have filters that refuse certain topics. This model removes that restriction. Freer use for research and development.

② Hermes Agent Specialization Fine-tuned on NousResearch's Hermes datasets, excellent at "AI using tools (function calling, agent behavior)." Ideal for automation and tool integration.

③ GGUF Format = Runs on Local PC GGUF is readable by inference software like llama.cpp. No cloud needed — put the model on your own PC and run it.

Basic Specs

Item	Value
Total parameters	35B (35 billion)
Active parameters	3B (MoE)
Format	GGUF (llama.cpp compatible)
Support	Text + images (multimodal)
License	apache-2.0
Recommended quantization	APEX quant (for RTX 3060 12GB)

Being an MoE (Mixture of Experts) model, total parameters are 35B, but only ~3B are actually computed. So it has "giant model knowledge" while running lightly.

How MoE Works Diagram

Why Run Locally?

Compared to cloud APIs (ChatGPT, etc.), local models have clear advantages:

Privacy: input data never leaves your machine
$0 running cost: unlimited use without API billing
Free customization: tune it to your liking
Offline: works without internet

Especially as an "uncensored" model, it suits developers who want to use AI freely under their own rules.

Required Specs

Reference for comfortable local running:

Quantization	Required VRAM	Reference GPU
Q4_K_M (recommended)	~12GB	RTX 3060 / 4070
Q5_K_M	~16GB	RTX 4060Ti / 4070Ti
Q8 / F16	24GB+	RTX 4090

Run with Ollama (Easiest)

# Pull the model
ollama pull qwen3.6-35b-genesis-hermes

# Run
ollama run qwen3.6-35b-genesis-hermes

Run with llama.cpp

# Build (with CUDA support)
cmake -B build -DGGML_CUDA=ON
cmake --build build --config Release

# Run (ngl 99 = use GPU as much as possible)
./build/bin/llama-cli \
  -m ./qwen3.6-35b.Q4_K_M.gguf \
  -p "Hello" \
  -n 512 \
  -ngl 99

-ngl 99 maximizes GPU usage. Lower it if VRAM is tight.

It Can Also Read Images (Multimodal)

This model supports image input. With llama.cpp's multimodal build, you can feed it photos and ask for explanations.

./llama-mtmd-cli -m ./model.gguf --mmproj ./mmproj.gguf -i image.png

Recommended Uses (My Ideas)

① As the core of a local AI agent Hermes-specialized means it's good at function calling and tool integration. Combine with agent frameworks like Hermes Agent to build your own automation assistant.

② Private research & development Uncensored, so it can handle specialized experiments and analysis that public models often refuse.

③ Offline writing & ideation Runs without network, so it works as a high-performance AI assistant while traveling or under data limits.

Caveats (Honest Downsides)

12GB VRAM runs it, but output speed depends on GPU: RTX 3060 is a bit slow
Multimodal needs extra files (mmproj)
Uncensored = responsibility: more freedom means self-managing ethical use
Chinese/English tend to be more accurate than Japanese (varies by task)

FAQ

Q1. Can I use it for free?

Yes. The model is Apache-2.0 licensed and free. llama.cpp is also open source.

Q2. Does it work on Mac?

Yes. llama.cpp supports Apple Silicon. It runs if you have enough RAM.

Q3. Can 8GB VRAM run it?

Light quantizations like Q2_K are possible, but for 35B-class, 12GB+ is recommended.

Q4. Is it smarter than ChatGPT?

Depends on the task. It wins on specific uses (agents, local, privacy-first), but general conversation quality may trail top cloud models.

Q5. Can it really read images?

Yes — with the multimodal build and mmproj file.

Summary

Qwen3.6-35B Genesis Hermes GGUF is the 2026 model to watch: "uncensored + Hermes-specialized + local operation" all in one.

Based on Alibaba Qwen3.6 MoE (35B total / 3B active)
Uncensored, free to use
Multimodal, reads images
Runs comfortably on your home PC with 12GB VRAM

For anyone serious about local AI, privacy, or building your own agent: try it now.