# Efficient reasoning

QVikhr-3-1.7B-Instruction-noreasoning is an instruction model based on Qwen/Qwen3-1.7B, trained on the Russian dataset GrandMaster2, and is specifically designed for efficient processing of Russian and English texts.

Qwen3-8B-AWQ is the latest generation of large language model with 8.2B parameters in the Tongyi Qianwen series, which uses AWQ 4-bit quantization technology to optimize inference efficiency. It supports the switching between thinking and non-thinking modes and has excellent reasoning, instruction-following, and intelligent agent capabilities.

Qwen2.5-VL-7B-Instruct-GPTQ-Int4 is an unofficial GPTQ-Int4 quantized version based on the Qwen2.5-VL-7B-Instruct model, supporting multimodal tasks from image-text to text.

Turkish large language model based on Gemma-2-9b developed by WiroAI, specializing in dialogue generation tasks

360 Zhinao is an open-source large language model series developed by Qihoo 360, including base models and dialogue models with various context lengths, supporting both Chinese and English.

A 7-billion-parameter small-scale reasoning model that outperforms larger models on multiple benchmarks