Instructions to use brittlewis12/s1-32B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use brittlewis12/s1-32B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="brittlewis12/s1-32B-GGUF",
	filename="s1-32b.IQ1_M.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use brittlewis12/s1-32B-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 brittlewis12/s1-32B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf brittlewis12/s1-32B-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 brittlewis12/s1-32B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf brittlewis12/s1-32B-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 brittlewis12/s1-32B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf brittlewis12/s1-32B-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 brittlewis12/s1-32B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf brittlewis12/s1-32B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/brittlewis12/s1-32B-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use brittlewis12/s1-32B-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "brittlewis12/s1-32B-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": "brittlewis12/s1-32B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/brittlewis12/s1-32B-GGUF:Q4_K_M

Ollama
How to use brittlewis12/s1-32B-GGUF with Ollama:
```
ollama run hf.co/brittlewis12/s1-32B-GGUF:Q4_K_M
```

Unsloth Studio

How to use brittlewis12/s1-32B-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for brittlewis12/s1-32B-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for brittlewis12/s1-32B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for brittlewis12/s1-32B-GGUF to start chatting

How to use brittlewis12/s1-32B-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf brittlewis12/s1-32B-GGUF:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "brittlewis12/s1-32B-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use brittlewis12/s1-32B-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 brittlewis12/s1-32B-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 brittlewis12/s1-32B-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat new

OpenClaw new

How to use brittlewis12/s1-32B-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf brittlewis12/s1-32B-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 "brittlewis12/s1-32B-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"

Docker Model Runner
How to use brittlewis12/s1-32B-GGUF with Docker Model Runner:
```
docker model run hf.co/brittlewis12/s1-32B-GGUF:Q4_K_M
```

Lemonade

How to use brittlewis12/s1-32B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull brittlewis12/s1-32B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.s1-32B-GGUF-Q4_K_M

List all available models

lemonade list

s1 32B GGUF

Update as of 2025-02-11: See the revised s1.1 for an improved model, based on DeepSeek R1 reasoning traces rather than Gemini traces.

Original model: s1 32B

Model creator: simplescaling

s1 is a reasoning model finetuned from Qwen2.5-32B-Instruct on just 1,000 examples. It matches o1-preview & exhibits test-time scaling via budget forcing.

This repo contains GGUF format model files for simplescaling’s s1 32B, an open reproduction of OpenAI’s o1-preview on 1,000 reasoning traces, including model, source code, and data (see s1K).

Learn more on simplescaling’s s1 github repo & arxiv preprint.

What is GGUF?

GGUF is a file format for representing AI models. It is the third version of the format, introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp. Converted with llama.cpp build 4628 (revision cde3833), using autogguf-rs.

Prompt template: ChatML

<|im_start|>system
{{system_message}}<|im_end|>
<|im_start|>user
{{prompt}}<|im_end|>
<|im_start|>assistant

Download & run with cnvrs on iPhone, iPad, and Mac!

cnvrs is the best app for private, local AI on your device:

create & save Characters with custom system prompts & temperature settings
download and experiment with any GGUF model you can find on HuggingFace!
- or, use an API key with the chat completions-compatible model provider of your choice -- ChatGPT, Claude, Gemini, DeepSeek, & more!
make it your own with custom Theme colors
powered by Metal ⚡️ & Llama.cpp, with haptics during response streaming!
try it out yourself today, on Testflight!
follow cnvrs on twitter to stay up to date

Original Model Evaluation

Table 1: s1-32B is an open and sample-efficient reasoning model. We evaluate s1-32B, Qwen, and Gemini (some entries are unknown (N.A.), see §4). Other results are from the respective reports (Qwen et al., 2024; Team, 2024b; OpenAI, 2024; DeepSeek-AI et al., 2025; Labs, 2025; Team, 2025).

# ex. = number examples used for reasoning finetuning; BF = budget forcing.

via s1: Simple test-time scaling (4.1 Results)

Model	# ex.	AIME 2024	MATH 500	GPQA Diamond
API only
o1-preview	N.A.	44.6	85.5	73.3
o1-mini	N.A.	70.0	90.0	60.0
o1	N.A.	74.4	94.8	77.3
Gemini 2.0 Flash Think.	N.A.	60.0	N.A.	N.A.
Open Weights
Qwen2.5-32B-Instruct	N.A.	26.7	84.0	49.0
QwQ-32B	N.A.	50.0	90.6	65.2
r1	>>800K	79.8	97.3	71.5
r1-distill	800K	72.6	94.3	62.1
Open Weights and Open Data
Sky-T1	17K	43.3	82.4	56.8
Bespoke-32B	17K	63.3	93.0	58.1
s1 w/o BF	1K	50.0	92.6	56.6
s1-32B	1K	56.7	93.0	59.6

Downloads last month: 176

GGUF

Model size

33B params

Architecture

qwen2

Hardware compatibility

1-bit

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

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Model tree for brittlewis12/s1-32B-GGUF

Base model

simplescaling/s1-32B

Quantized

(11)

this model

Dataset used to train brittlewis12/s1-32B-GGUF

Paper for brittlewis12/s1-32B-GGUF

s1: Simple test-time scaling

Paper • 2501.19393 • Published Jan 31, 2025 • 126