# High-Precision Reasoning

The Gemma 3 4B IT model by Google supports multimodal input and long-context processing, suitable for text generation and image understanding tasks.

ReasonFlux-F1-7B is a hierarchical large language model reasoning model based on thinking template expansion, fine-tuned through template-enhanced reasoning trajectories, demonstrating outstanding performance in multiple reasoning tasks.

A model trained through reinforcement fine-tuning based on Qwen 2.5 32B Instruct, specifically designed to solve challenging deductive reasoning problems in the Temporal Clue dataset.

Phi-4-Model-Stock-v2 is a large language model merged from multiple Phi-4 variant models using the model_stock merging method, demonstrating strong performance across multiple benchmarks.

The next-generation 72B-parameter large language model from Tongyi Qianwen, supporting 131K long text processing, with excellent performance in language understanding, text generation, programming, and mathematical reasoning

Yi-34B-Chat is a bilingual large language model developed by 01.AI, excelling in language understanding, commonsense reasoning, and reading comprehension, supporting both Chinese and English interactions.

Yi-34B-Chat is a next-generation open-source bilingual large language model trained by 01.AI, excelling in language understanding, commonsense reasoning, reading comprehension, and is one of the most powerful LLMs globally.