Instructions to use abenzerps/Apodex-1.1-mini-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 abenzerps/Apodex-1.1-mini-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 abenzerps/Apodex-1.1-mini-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf abenzerps/Apodex-1.1-mini-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf abenzerps/Apodex-1.1-mini-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf abenzerps/Apodex-1.1-mini-GGUF:Q4_K_M

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 abenzerps/Apodex-1.1-mini-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf abenzerps/Apodex-1.1-mini-GGUF:Q4_K_M

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 abenzerps/Apodex-1.1-mini-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf abenzerps/Apodex-1.1-mini-GGUF:Q4_K_M

Use Docker

docker model run hf.co/abenzerps/Apodex-1.1-mini-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use abenzerps/Apodex-1.1-mini-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "abenzerps/Apodex-1.1-mini-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": "abenzerps/Apodex-1.1-mini-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/abenzerps/Apodex-1.1-mini-GGUF:Q4_K_M

Ollama
How to use abenzerps/Apodex-1.1-mini-GGUF with Ollama:
```
ollama run hf.co/abenzerps/Apodex-1.1-mini-GGUF:Q4_K_M
```
Unsloth Desktop

How to use abenzerps/Apodex-1.1-mini-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf abenzerps/Apodex-1.1-mini-GGUF:Q4_K_M

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": "abenzerps/Apodex-1.1-mini-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use abenzerps/Apodex-1.1-mini-GGUF with Docker Model Runner:
```
docker model run hf.co/abenzerps/Apodex-1.1-mini-GGUF:Q4_K_M
```

Lemonade

How to use abenzerps/Apodex-1.1-mini-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull abenzerps/Apodex-1.1-mini-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Apodex-1.1-mini-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use abenzerps/Apodex-1.1-mini-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 abenzerps/Apodex-1.1-mini-GGUF:Q4_K_M

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 abenzerps/Apodex-1.1-mini-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use abenzerps/Apodex-1.1-mini-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf abenzerps/Apodex-1.1-mini-GGUF:Q4_K_M

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 "abenzerps/Apodex-1.1-mini-GGUF:Q4_K_M" \
  --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"

Apodex-1.1-mini GGUF

GGUF quantizations of apodex/Apodex-1.1-mini, a 35.95B-parameter Qwen3.5 MoE model for research, data, files, code, and tool-driven work.

All model files retain the checkpoint's native MTP/NextN head. For image input, use the included F16 vision projector.

Upstream benchmarks

Results reported by Apodex AI from evaluations of the original Apodex-1.1 model using FrontierAgent, its agent harness and evaluation suite.

Results reported by Apodex AI from evaluations of the original Apodex-1.1-mini checkpoint using FrontierAgent. With the Agent Team workflow, it scored 27.7 on APEX-Agent, 50.2 on FrontierFinance, and 51.7 on FrontierScience-Research.

GGUF files

Quantization	File	Size	Notes
IQ1_M	Apodex-1.1-mini-IQ1_M.gguf	8.82 GB	Ultra-low-memory option
IQ2_M	Apodex-1.1-mini-IQ2_M.gguf	12.2 GB	Smallest recommended option
Q2_K	Apodex-1.1-mini-Q2_K.gguf	13.2 GB	Maximum-compression K-quant
IQ3_M	Apodex-1.1-mini-IQ3_M.gguf	16.0 GB	Importance-aware compact option
Q3_K_M	Apodex-1.1-mini-Q3_K_M.gguf	17.2 GB	Standard Q3 K-quant
Q4 Selective	Apodex-1.1-mini-Q4_Selective-Q4_K_M.gguf	19.8 GB	Compact custom Q4 alternative
Q4_K_S	Apodex-1.1-mini-Q4_K_S.gguf	20.4 GB	Smaller Q4 option
Q4_K_M	Apodex-1.1-mini-Q4_K_M.gguf	21.7 GB	Recommended default
Q5_K_S	Apodex-1.1-mini-Q5_K_S.gguf	24.6 GB	Smaller Q5 option
Q5_K_M	Apodex-1.1-mini-Q5_K_M.gguf	25.3 GB	Higher-quality Q5 option
Q6_K	Apodex-1.1-mini-Q6_K.gguf	29.2 GB	High-quality option
Q8_0	Apodex-1.1-mini-Q8_0.gguf	37.8 GB	Near-lossless reference quantization
Vision projector	mmproj-Apodex-1.1-mini-F16.gguf	899 MB	Required for image input

The IQ builds use the included importance matrix. Q4 Selective is a compact custom Q4 alternative that selectively retains higher precision in key weights.

Usage

Use a current llama.cpp build with the included chat template.

llama-cli \
  -m Apodex-1.1-mini-Q4_K_M.gguf \
  -c 4096 -n 512 --temp 1.0 --top-p 0.95 \
  --jinja --chat-template-file chat_template.jinja \
  -p "Explain why reproducible builds matter."

For MTP speculative decoding:

llama-server \
  -m Apodex-1.1-mini-Q4_K_M.gguf \
  --spec-type draft-mtp --spec-draft-n-max 3 \
  --jinja --chat-template-file chat_template.jinja

For image input:

llama-mtmd-cli \
  -m Apodex-1.1-mini-Q4_K_M.gguf \
  -mm mmproj-Apodex-1.1-mini-F16.gguf \
  --image image.jpg -p "Describe this image."

Source

Model: apodex/Apodex-1.1-mini
Chat template revision: 62583b4
License: Apache-2.0
Checksums: SHA256SUMS

Downloads last month: 25,335

GGUF

Model size

36B params

Architecture

qwen35moe

Hardware compatibility

1-bit

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

Model tree for abenzerps/Apodex-1.1-mini-GGUF

Base model

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

Finetuned

Qwen/Qwen3.5-35B-A3B

Finetuned

apodex/Apodex-1.1-mini

Quantized

(19)

this model

Collection including abenzerps/Apodex-1.1-mini-GGUF

Apodex-1.1-mini

Collection

Apodex-1.1-mini model family releases, including GGUF and MLX conversions. • 2 items • Updated 4 days ago