OpenThinker-7B and OpenThinker-32B are cutting-edge models designed to push the boundaries of structured reasoning, mathematical problem-solving, and knowledge-based inference. Fine-tuned on the OpenThoughts-114k dataset, these models build upon Qwen2.5-7B and Qwen2.5-32B, leveraging optimized training methodologies to achieve remarkable accuracy in logical tasks and long-form reasoning.

🔹 OpenThinker-7B strikes the perfect balance between efficiency and performance, making it ideal for research, structured problem-solving, and academic applications.

🔹 OpenThinker-32B is optimized for deep contextual understanding, theorem proving, and large-scale reasoning, delivering state-of-the-art precision in computational workflows.

We just published a comprehensive step-by-step guide on how to install and run these models locally on GPU-powered virtual machines! Whether you prefer Ollama, Open WebUI, or Jupyter Notebook, we’ve covered everything you need to deploy and interact with these models seamlessly.

🛠️ Key highlights of our blog:
✅ Hardware requirements & best GPU configurations
✅ Running OpenThinker-7B & 32B using Ollama
✅ Using Open WebUI for seamless interaction
✅ Running inference & fine-tuning on Jupyter Notebook

With complete transparency in weights, datasets, and training methodologies, OpenThinker models are setting new standards for open-source computational reasoning. Released under the Apache 2.0 License, these models are available for researchers and developers to modify, fine-tune, and scale for real-world applications.

Read the full blog here: https://t.co/3i8qcGejxc

#openthinker #OpenSource #AIModels #Cloud #gpus