Qwen3 8B Q5 K M
Qwen3-8B in Q5KM GGUF format for CPU/GPU inference with llama.cpp or llama-cpp-python.
Model source
- Kind
- Other
- File size
- 5.45 GB
- Base model
- Qwen/Qwen3-8B
- Version
- vQwen3 8 B Q5 K M
- Updated
- Oct 18, 2026
- Source
- Hugging Face
Source description
Qwen3-8B-Q5_K_M
Qwen3-8B in Q5_K_M GGUF format for CPU/GPU inference with llama.cpp or llama-cpp-python.
- Source base model: Qwen/Qwen3-8B
- Original GGUF source: Qwen/Qwen3-8B-GGUF
- Quantization: Q5_K_M (~5.85 GB)
- License: Apache 2.0
Usage
py -3.11 -m pip install llama-cpp-python transformers
from llama_cpp import Llama
from transformers import AutoTokenizer
llm = Llama(model_path="Qwen3-8B-Q5_K_M.gguf", n_ctx=8192)
tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen3-8B")
messages = [{"role": "user", "content": "Hello!"}]
prompt = tokenizer.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True, enable_thinking=False
)
out = llm(prompt, max_tokens=256, stop=[tokenizer.eos_token])
print(out["choices"][0]["text"])
Sources
1 source
Sources
1 sourceVerified Oct 18
Model artifacts
1 artifact
Model artifacts
1 artifactSource excerpts
3 excerpts
Source excerpts
3 excerpts--- license: apache-2.0 base_model: Qwen/Qwen3-8B tags: - gguf - qwen3 - q5_k_m - text-generation library_name: llama-cpp-python --- # Qwen3-8B-Q5_K_M Qwen3-8B in **Q5_K_M** GGUF format for CPU/GPU inference with llama.cpp or llama-cpp-python. - Source base model: [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B) - Original GGUF source: [Qwen/Qwen3-8B-GGUF](https://huggingface.co/Qwen/Qwen3-8B-GGUF) - Quantization: Q5_K_M (~5.85 GB) - License: Apache 2.0 ## Usage ```powershell py -3.11 -m pip install llama-cpp-python transformers ``` ```python from llama_cpp import Llama from transformers import AutoTokenizer llm = Llama(model_path="Qwen3-8B-Q5_K_M.gguf", n_ctx=8192) tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen3-8B") messages = [{"role": "user", "content": "Hello!"}] prompt = tokenizer.apply_chat_template( messages, tokenize=False, add_generation_prompt=True, enable_thinking=False ) out = llm(prompt, max_tokens=256, stop=[tokenizer.eos_token]) print(out["choices"][0]["text"]) ```
Source context: 60 downloads · 0 likes · Pipeline text-generation · Library llama-cpp-python · Repo Mukilan06/Qwen3-8B-Q5_K_M
Source context: 20 downloads · 0 likes · Pipeline text-generation · Library llama-cpp-python · Repo Mukilan06/Qwen3-8B-Q5_K_M
