TeichAI/Qwen3-4B-Thinking-2507-GPT-5.1-Codex-Max-Distill
TeichAI/Qwen3-4B-Thinking-2507-GPT-5.1-Codex-Max-Distill is a 4 billion parameter Qwen3 model developed by TeichAI, fine-tuned from unsloth/qwen3-4b-thinking-2507. This model was trained 2x faster using Unsloth and Huggingface's TRL library, indicating an optimization for efficient training. With a 32768 token context length, it is designed for applications requiring substantial input processing. Its specific "Thinking" and "Codex Max Distill" naming suggests a focus on reasoning capabilities and code-related tasks.
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Overview
TeichAI/Qwen3-4B-Thinking-2507-GPT-5.1-Codex-Max-Distill is a 4 billion parameter Qwen3-based language model developed by TeichAI. It is fine-tuned from the unsloth/qwen3-4b-thinking-2507 model, leveraging Unsloth and Huggingface's TRL library for accelerated training. This optimization allowed the model to be trained 2x faster, highlighting an emphasis on efficiency in its development.
Key Capabilities
- Efficient Training: Developed with Unsloth and Huggingface's TRL library, enabling 2x faster training.
- Qwen3 Architecture: Based on the Qwen3 model family, providing a robust foundation.
- Context Length: Supports a substantial context window of 32768 tokens, suitable for processing longer inputs.
Good For
- Applications requiring a 4 billion parameter model with a focus on efficient training.
- Use cases that benefit from the Qwen3 architecture and a large context window.
- Developers interested in models optimized with Unsloth for faster iteration cycles.