Instructions to use brittlewis12/DeepSeek-R1-0528-Qwen3-8B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use brittlewis12/DeepSeek-R1-0528-Qwen3-8B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="brittlewis12/DeepSeek-R1-0528-Qwen3-8B-GGUF",
	filename="deepseek-r1-0528-qwen3-8b.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/DeepSeek-R1-0528-Qwen3-8B-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf brittlewis12/DeepSeek-R1-0528-Qwen3-8B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf brittlewis12/DeepSeek-R1-0528-Qwen3-8B-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf brittlewis12/DeepSeek-R1-0528-Qwen3-8B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf brittlewis12/DeepSeek-R1-0528-Qwen3-8B-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/DeepSeek-R1-0528-Qwen3-8B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf brittlewis12/DeepSeek-R1-0528-Qwen3-8B-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/DeepSeek-R1-0528-Qwen3-8B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf brittlewis12/DeepSeek-R1-0528-Qwen3-8B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/brittlewis12/DeepSeek-R1-0528-Qwen3-8B-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use brittlewis12/DeepSeek-R1-0528-Qwen3-8B-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "brittlewis12/DeepSeek-R1-0528-Qwen3-8B-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/DeepSeek-R1-0528-Qwen3-8B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/brittlewis12/DeepSeek-R1-0528-Qwen3-8B-GGUF:Q4_K_M

Ollama
How to use brittlewis12/DeepSeek-R1-0528-Qwen3-8B-GGUF with Ollama:
```
ollama run hf.co/brittlewis12/DeepSeek-R1-0528-Qwen3-8B-GGUF:Q4_K_M
```

Unsloth Studio

How to use brittlewis12/DeepSeek-R1-0528-Qwen3-8B-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/DeepSeek-R1-0528-Qwen3-8B-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/DeepSeek-R1-0528-Qwen3-8B-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/DeepSeek-R1-0528-Qwen3-8B-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use brittlewis12/DeepSeek-R1-0528-Qwen3-8B-GGUF with Docker Model Runner:
```
docker model run hf.co/brittlewis12/DeepSeek-R1-0528-Qwen3-8B-GGUF:Q4_K_M
```

Lemonade

How to use brittlewis12/DeepSeek-R1-0528-Qwen3-8B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull brittlewis12/DeepSeek-R1-0528-Qwen3-8B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.DeepSeek-R1-0528-Qwen3-8B-GGUF-Q4_K_M

List all available models

lemonade list

DeepSeek R1 0528 Qwen3 8B GGUF

Original model: DeepSeek-R1-0528-Qwen3-8B

Model creator: DeepSeek AI

We distilled the chain-of-thought from DeepSeek-R1-0528 to post-train Qwen3 8B Base, obtaining DeepSeek-R1-0528-Qwen3-8B. This model achieves state-of-the-art (SOTA) performance among open-source models on the AIME 2024, surpassing Qwen3 8B by +10.0% and matching the performance of Qwen3-235B-thinking. We believe that the chain-of-thought from DeepSeek-R1-0528 will hold significant importance for both academic research on reasoning models and industrial development focused on small-scale models.

This repo contains GGUF format model files for DeepSeek AI's DeepSeek R1 0528 Qwen3 8B.

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.

Converted with llama.cpp build b5536 (revision 2b13162), using autogguf-rs.

Prompt template: DeepSeek R1

{{system_message}}

<｜User｜>{{prompt}}<｜Assistant｜>

Notes from DeepSeek on Running Locally

Compared to previous versions of DeepSeek-R1, the usage recommendations for DeepSeek-R1-0528 have the following changes:

System prompt is supported now.

It is not required to add <think>\n at the beginning of the output to force the model into thinking pattern.

The model architecture of DeepSeek-R1-0528-Qwen3-8B is identical to that of Qwen3-8B, but it shares the same tokenizer configuration as DeepSeek-R1-0528.

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!
- if you already have the app, download DeepSeek R1 0528 Qwen3 8B now!
- cnvrsai:///models/search/hf?id=brittlewis12/DeepSeek-R1-0528-Qwen3-8B-GGUF
follow cnvrs on twitter to stay up to date

Original Model Evaluation

We distilled the chain-of-thought from DeepSeek-R1-0528 to post-train Qwen3 8B Base, obtaining DeepSeek-R1-0528-Qwen3-8B. This model achieves state-of-the-art (SOTA) performance among open-source models on the AIME 2024, surpassing Qwen3 8B by +10.0% and matching the performance of Qwen3-235B-thinking.

	AIME 24	AIME 25	HMMT Feb 25	GPQA Diamond	LiveCodeBench (2408-2505)
Qwen3-235B-A22B	85.7	81.5	62.5	71.1	66.5
Qwen3-32B	81.4	72.9	-	68.4	-
Qwen3-8B	76.0	67.3	-	62.0	-
Phi-4-Reasoning-Plus-14B	81.3	78.0	53.6	69.3	-
Gemini-2.5-Flash-Thinking-0520	82.3	72.0	64.2	82.8	62.3
o3-mini (medium)	79.6	76.7	53.3	76.8	65.9
DeepSeek-R1-0528-Qwen3-8B	86.0	76.3	61.5	61.1	60.5

DeepSeek R1 0528 Qwen3 8B in cnvrs on iOS

Downloads last month: 399

GGUF

Model size

8B params

Architecture

qwen3

Hardware compatibility

1-bit

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3-bit

4-bit

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6-bit

8-bit

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Model tree for brittlewis12/DeepSeek-R1-0528-Qwen3-8B-GGUF

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deepseek-ai/DeepSeek-R1-0528-Qwen3-8B

Quantized

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