Instructions to use peasantsmith/gpt-oss-120b-PS-IQ4_NL.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 peasantsmith/gpt-oss-120b-PS-IQ4_NL.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 peasantsmith/gpt-oss-120b-PS-IQ4_NL.gguf:IQ4_NL
# Run inference directly in the terminal:
llama cli -hf peasantsmith/gpt-oss-120b-PS-IQ4_NL.gguf:IQ4_NL

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf peasantsmith/gpt-oss-120b-PS-IQ4_NL.gguf:IQ4_NL
# Run inference directly in the terminal:
llama cli -hf peasantsmith/gpt-oss-120b-PS-IQ4_NL.gguf:IQ4_NL

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 peasantsmith/gpt-oss-120b-PS-IQ4_NL.gguf:IQ4_NL
# Run inference directly in the terminal:
./llama-cli -hf peasantsmith/gpt-oss-120b-PS-IQ4_NL.gguf:IQ4_NL

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 peasantsmith/gpt-oss-120b-PS-IQ4_NL.gguf:IQ4_NL
# Run inference directly in the terminal:
./build/bin/llama-cli -hf peasantsmith/gpt-oss-120b-PS-IQ4_NL.gguf:IQ4_NL

Use Docker

docker model run hf.co/peasantsmith/gpt-oss-120b-PS-IQ4_NL.gguf:IQ4_NL

LM Studio
Jan

vLLM

How to use peasantsmith/gpt-oss-120b-PS-IQ4_NL.gguf with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "peasantsmith/gpt-oss-120b-PS-IQ4_NL.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": "peasantsmith/gpt-oss-120b-PS-IQ4_NL.gguf",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/peasantsmith/gpt-oss-120b-PS-IQ4_NL.gguf:IQ4_NL

Ollama
How to use peasantsmith/gpt-oss-120b-PS-IQ4_NL.gguf with Ollama:
```
ollama run hf.co/peasantsmith/gpt-oss-120b-PS-IQ4_NL.gguf:IQ4_NL
```
Unsloth Desktop

How to use peasantsmith/gpt-oss-120b-PS-IQ4_NL.gguf with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf peasantsmith/gpt-oss-120b-PS-IQ4_NL.gguf:IQ4_NL

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": "peasantsmith/gpt-oss-120b-PS-IQ4_NL.gguf:IQ4_NL"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use peasantsmith/gpt-oss-120b-PS-IQ4_NL.gguf with Docker Model Runner:
```
docker model run hf.co/peasantsmith/gpt-oss-120b-PS-IQ4_NL.gguf:IQ4_NL
```

Lemonade

How to use peasantsmith/gpt-oss-120b-PS-IQ4_NL.gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull peasantsmith/gpt-oss-120b-PS-IQ4_NL.gguf:IQ4_NL

Run and chat with the model

lemonade run user.gpt-oss-120b-PS-IQ4_NL.gguf-IQ4_NL

List all available models

lemonade list

Hermes Agent

How to use peasantsmith/gpt-oss-120b-PS-IQ4_NL.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 peasantsmith/gpt-oss-120b-PS-IQ4_NL.gguf:IQ4_NL

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 peasantsmith/gpt-oss-120b-PS-IQ4_NL.gguf:IQ4_NL

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use peasantsmith/gpt-oss-120b-PS-IQ4_NL.gguf with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf peasantsmith/gpt-oss-120b-PS-IQ4_NL.gguf:IQ4_NL

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 "peasantsmith/gpt-oss-120b-PS-IQ4_NL.gguf:IQ4_NL" \
  --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"

gpt-oss-120b-PS-GGUF

GGUF quantizations of gpt-oss-120b by PeasantSmith & BlackFrost AI.

Quantization	BPW	Size	Quantizer
IQ4_NL	4.91	71.75GB	Peasant Smith
IQ2_XXS	2.x	66.1GB	BlackFrost AI

Testing

Raw perplexity doesn't work here: gpt-oss needs the harmony response format, and even the F16 source returns NaN on unformatted text past chunk 8. Validated with task-based tests instead: Quantization quality was validated with task-based tests instead:

Test	Result
Greedy generation (factual question)	PASS, correct answer + complete reasoning block
LRU cache implementation task (8192 ctx)	PASS, doubly-linked-list, O(1) get/put, coherent
Needle recall (magic value 9137@8k ctx)	PASS, exact answer: `9137`
Runtime errors	0

Recommended parameters

Temperature: 1.0
Top-k: 0 (i.e. all)
Top-p: 1.0

Example llama.cpp invocation:

llama-cli -m gpt-oss-120b-IQ4_NL.gguf \
  -c 8192 -fa -ngl 99 -ncmoe 36 \
  --split-mode layer --tensor-split 1,1,1 \
  --temp 1.0 --top-k 0 --top-p 1.0

Flag names vary across llama.cpp builds.

Reproduce/Verify

llama-quantize \
  --tensor-type "ffn_gate_exps=iq4_nl" \
  --tensor-type "ffn_up_exps=iq4_nl" \
  --tensor-type "ffn_down_exps=q5_0" \
  --token-embedding-type q8_0 \
  gpt-oss-120b-F16.gguf gpt-oss-120b-IQ4_NL.gguf q8_0

License

Quantized derivative of gpt-oss-120b: license and usage terms follow upstream, verify before redistribution. Base model by OpenAI.

Additional information

The quantization is released under the PeasantSmith (PS) signature, reflected in the repository name gpt-oss-120b-PS-GGUF. Individual GGUF files use the standard model-<quant>.gguf naming (e.g. gpt-oss-120b-IQ4_NL.gguf) so Ollama and HuggingFace quant-tag parsing work correctly. The IQ4_NL label identifies this specific quantized release and should not be confused with the upstream model's original naming.

Downloads last month: 963

GGUF

Model size

117B params

Architecture

gpt-oss

Hardware compatibility

4-bit

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