TeichAI/Qwen3-4B-Thinking-2507-Gemini-3-Pro-Preview-High-Reasoning-Distill
TeichAI/Qwen3-4B-Thinking-2507-Gemini-3-Pro-Preview-High-Reasoning-Distill is a 4 billion parameter language model developed by TeichAI, based on the Qwen3 architecture. It was specifically trained on a Gemini 3 Pro Preview dataset with a focus on high reasoning effort. This model is optimized for tasks requiring strong analytical capabilities, particularly in coding and scientific domains, and features a 40960 token context length.
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Model Overview
TeichAI/Qwen3-4B-Thinking-2507-Gemini-3-Pro-Preview-High-Reasoning-Distill is a 4 billion parameter language model from TeichAI, built upon the unsloth/Qwen3-4B-Thinking-2507 base model. Its key differentiator is its training on a specialized Gemini 3 Pro Preview dataset engineered for high reasoning effort.
Key Capabilities
- Enhanced Reasoning: The model's training on a high-reasoning dataset suggests improved performance on complex analytical tasks.
- Specialized Training Data: Utilizes the
TeichAI/gemini-3-pro-preview-high-reasoning-250xdataset, indicating a focus on advanced problem-solving.
Good For
This model is particularly well-suited for use cases in:
- Coding: Its reasoning-focused training can benefit code generation, debugging, and understanding complex programming logic.
- Science: Applicable to scientific problem-solving, data analysis, and understanding scientific concepts where high reasoning is crucial.
Training Details
The training process involved a dataset with 2.73 million total tokens (input + output) and incurred a cost of $32.7 USD, highlighting a targeted and efficient training approach for its specific reasoning objective.