Instructions to use batiai/Qwen3.5-35B-A3B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use batiai/Qwen3.5-35B-A3B-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf batiai/Qwen3.5-35B-A3B-GGUF:IQ4_XS
# Run inference directly in the terminal:
llama cli -hf batiai/Qwen3.5-35B-A3B-GGUF:IQ4_XS

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf batiai/Qwen3.5-35B-A3B-GGUF:IQ4_XS
# Run inference directly in the terminal:
llama cli -hf batiai/Qwen3.5-35B-A3B-GGUF:IQ4_XS

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf batiai/Qwen3.5-35B-A3B-GGUF:IQ4_XS
# Run inference directly in the terminal:
./llama-cli -hf batiai/Qwen3.5-35B-A3B-GGUF:IQ4_XS

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf batiai/Qwen3.5-35B-A3B-GGUF:IQ4_XS
# Run inference directly in the terminal:
./build/bin/llama-cli -hf batiai/Qwen3.5-35B-A3B-GGUF:IQ4_XS

Use Docker

docker model run hf.co/batiai/Qwen3.5-35B-A3B-GGUF:IQ4_XS

LM Studio
Jan

vLLM

How to use batiai/Qwen3.5-35B-A3B-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "batiai/Qwen3.5-35B-A3B-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "batiai/Qwen3.5-35B-A3B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/batiai/Qwen3.5-35B-A3B-GGUF:IQ4_XS

Ollama
How to use batiai/Qwen3.5-35B-A3B-GGUF with Ollama:
```
ollama run hf.co/batiai/Qwen3.5-35B-A3B-GGUF:IQ4_XS
```
Unsloth Desktop

How to use batiai/Qwen3.5-35B-A3B-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf batiai/Qwen3.5-35B-A3B-GGUF:IQ4_XS

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "batiai/Qwen3.5-35B-A3B-GGUF:IQ4_XS"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use batiai/Qwen3.5-35B-A3B-GGUF with Docker Model Runner:
```
docker model run hf.co/batiai/Qwen3.5-35B-A3B-GGUF:IQ4_XS
```

Lemonade

How to use batiai/Qwen3.5-35B-A3B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull batiai/Qwen3.5-35B-A3B-GGUF:IQ4_XS

Run and chat with the model

lemonade run user.Qwen3.5-35B-A3B-GGUF-IQ4_XS

List all available models

lemonade list

Hermes Agent

How to use batiai/Qwen3.5-35B-A3B-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf batiai/Qwen3.5-35B-A3B-GGUF:IQ4_XS

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default batiai/Qwen3.5-35B-A3B-GGUF:IQ4_XS

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use batiai/Qwen3.5-35B-A3B-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf batiai/Qwen3.5-35B-A3B-GGUF:IQ4_XS

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "batiai/Qwen3.5-35B-A3B-GGUF:IQ4_XS" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

Qwen 3.5 35B-A3B GGUF — Quantized by BatiAI

IQ4_XS quantization of Qwen/Qwen3.5-35B-A3B for on-device AI on Mac. Built and verified by BatiAI for BatiFlow.

Quick Start

ollama pull batiai/qwen3.5-35b:iq4

Available Quantizations

Quant	Size	VRAM	M4 Max (128GB)	Recommended For
IQ4_XS	17GB	23GB	26.6 t/s	36GB+ Mac

Why MoE Beats Dense

35B-A3B is a Mixture-of-Experts model — 35B total, only 3B active per token:

	35B-A3B (MoE)	27B (Dense)
Total params	35B	27B
Active params	3B	27B
VRAM	23GB	28GB
Speed	26.6 t/s	17.0 t/s

MoE activates 9x fewer parameters — same quality, much faster, less memory.

Benchmarks — M4 Max (128GB)

Metric	IQ4_XS
Token generation	26.6 t/s
Korean	✅
Tool call JSON	✅
VRAM	23 GB

Full BatiAI Qwen 3.5 Lineup

Model	Size	VRAM	Speed	Min Mac
batiai/qwen3.5-9b:q4	5.2GB	~8GB	12.5 t/s	16GB
batiai/qwen3.5-27b:iq4	14GB	28GB	17.0 t/s	32GB
batiai/qwen3.5-35b:iq4	17GB	23GB	26.6 t/s	36GB

Technical Details

Original Model: Qwen/Qwen3.5-35B-A3B
Architecture: MoE (35B total, 3B active, 256 experts, 8 routed + 1 shared)
Context Window: 262K tokens
License: Apache 2.0
Quantized with: llama.cpp (build 400ac8e)

About BatiFlow

BatiFlow — free, on-device AI automation for Mac. 5MB app, 100% local, unlimited.

License

Quantized from Qwen/Qwen3.5-35B-A3B. License: Apache 2.0.

Benchmarks

Machine	Quant	Cold start	Prompt eval	Token gen	Tested
MacBook Pro M4 Max 128GB	IQ4_XS	4.825s	205.28 t/s	44.77 t/s	2026-05-03

Downloads last month: 53

GGUF

Model size

35B params

Architecture

qwen35moe

Hardware compatibility

4-bit

Model tree for batiai/Qwen3.5-35B-A3B-GGUF

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Qwen/Qwen3.5-35B-A3B-Base

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