tinyopsec/OctoThinker-8B-Long-Base-GGUF

OctoThinker-8B-Long-Base GGUF

GGUF quantizations of OctoThinker/OctoThinker-8B-Long-Base.

OctoThinker-8B-Long-Base is a mid-trained language model built on the Llama-3 family, designed to create a reinforcement learning–friendly base language model. It is trained using the Stable-then-Decay two-stage mid-training paradigm on large-scale mathematical datasets (MegaMath-Web-Pro-Max) and diversified Long Chain-of-Thought data, ensuring rapid convergence and improved RL stability.

For more details, see the paper.

Available Quantizations

VRAM Requirements

Usage

llama.cpp

./llama-cli -m model_q4_k_m.gguf -p "Your prompt here" -n 512

llama-cpp-python

from llama_cpp import Llama

llm = Llama(model_path="model_q4_k_m.gguf", n_ctx=8192)
output = llm("Your prompt here", max_tokens=512)
print(output["choices"][0]["text"])

LM Studio

Download the desired .gguf file and load it directly in LM Studio.

Ollama

ollama run hf.co/tinyopsec/OctoThinker-8B-Long-Base-GGUF

Citation

@article{wang2025octothinker,
  title={OctoThinker: Mid-training Incentivizes Reinforcement Learning Scaling},
  author={Wang, Zengzhi and Zhou, Fan and Li, Xuefeng and Liu, Pengfei},
  year={2025},
  journal={arXiv preprint arXiv:2506.20512},
  note={Preprint}
}