# Chain-of-Thought Optimization

FairyR1-32B is an efficient large language model developed by Peking University DS-LAB, based on DeepSeek-R1-Distill-Qwen-32B. It achieves a balance between high performance and low-cost inference through an innovative 'distillation-fusion' process.

A fine-tuned version of the Qwen3-30B-A3B mixture of experts model, with activated experts increased to 16 and context window expanded to 128k, suitable for complex reasoning scenarios

360 Zhinao 3-7B-O1.5 is a long chain-of-thought model open-sourced by Qihoo 360, fine-tuned based on 360 Zhinao 3-7B-Instruct, supporting complex reasoning tasks.

MAI-DS-R1 is the result of Microsoft AI team's post-training of the DeepSeek-R1 inference model, aimed at enhancing its response capability to sensitive topics and optimizing risk performance, while maintaining the original reasoning ability and competitive advantages.

A medical chain-of-thought reasoning model fine-tuned from DeepSeek-R1-Distill-Llama-8B, enhanced with QLoRA quantization and Unsloth optimization for medical reasoning.

AceMath-7B-Instruct is a specialized instruction model for mathematical reasoning developed by NVIDIA, based on an improved Qwen architecture, excelling at solving English math problems through chain-of-thought (CoT) reasoning.

LlamaV-o1 is an advanced multimodal large language model specifically designed for complex visual reasoning tasks, optimized through curriculum learning techniques, demonstrating outstanding performance across diverse benchmarks.

Enhances the reasoning generalization capabilities of large language models through reinforcement fine-tuning, based on Codellama fine-tuning, suitable for code generation and comprehension tasks.

Llemma 34B is a language model specialized in mathematics, initialized with Code Llama 34B weights and trained on the Proof-Pile-2 dataset.

This model is a merge of huggyllama/llama-30b and kaiokendev/SuperCOT-LoRA, optimized for use with LangChain prompts, particularly suitable for logical reasoning and step-by-step thinking tasks.