OpenThinker - Agent - v1 is an open - source intelligent agent model that is subsequently trained based on Qwen3 - 8B. It is designed for terminal operations and software engineering tasks. It is first trained on a high - quality supervised fine - tuning dataset and then further optimized through reinforcement learning. It performs excellently in agent benchmark tests such as Terminal - Bench 2.0 and SWE - Bench.

Natural Language ProcessingTransformersOther

Fyodor-Q3-8B-Instruct is a high-fidelity instruction-tuned model designed for intelligent reasoning and robust code generation. It is based on the Qwen3-8B architecture and trained with a high-rank LoRA configuration. It excels in planning before coding and is well-suited for complex software engineering tasks.

Natural Language ProcessingTransformersMultiple Languages

This is a pre-trained language model that merges Vistral-24B-Instruct and Cydonia-24B-v4.2.0 using the SLERP method, specifically optimized to support bilingual processing capabilities in Russian and English. The model intelligently combines the advantages of the two base models, enhancing English performance while maintaining Russian capabilities.

Natural Language ProcessingTransformersMultiple Languages

PokeeResearch-7B is a 7-billion-parameter deep research intelligent agent developed by Pokee AI. It combines reinforcement learning based on AI feedback (RLAIF) with an inference framework and can execute complex multi-step research workflows, including self-correction, verification, and comprehensive analysis.

Natural Language ProcessingTransformersEnglish

The Dorado Network Surfing Tool Extended Version is a function call and intelligent reasoning model fine-tuned based on Tongyi Qianwen 3 - 4B. It is designed for network search orchestration, tool-enhanced reasoning, and dynamic problem solving. It excels in intelligent decision-making, tool selection, and structured execution processes.

Natural Language ProcessingTransformersEnglish

Instinct is a code editing model based on Qwen2.5-Coder-7B. It has been fine-tuned on real-world code editing datasets and can intelligently predict the developer's next operation to maintain a smooth programming state. This GGUF quantized version is created by QuantFactory and provides efficient local inference capabilities.

Natural Language ProcessingTransformers

Jan-v1-AIO-GGUF contains two powerful language models: Jan-v1-4B and Jan-v1-edge. Jan-v1-4B is based on the Qwen3-4B-thinking architecture, with 4 billion parameters. It has strong intelligent reasoning, problem-solving, and tool-using capabilities and supports web search tasks. Jan-v1-edge is a lightweight intelligent model designed for fast execution on devices and is suitable for resource-constrained environments.

Natural Language ProcessingTransformersEnglish

Instinct is the most advanced open next-editing model launched by Continue. Based on the Qwen2.5-Coder-7B model, it has been robustly fine-tuned on real-world code editing datasets and can intelligently predict the developer's next operation.

Natural Language ProcessingTransformers

DeepSeek-V3.1 is a large language model that is post-trained based on DeepSeek-V3.1-Base. It has a 128K context length and supports mixed thinking modes, intelligent tool invocation, and code proxy functions. This model performs excellently in multiple benchmark tests, especially showing significant improvements in mathematical reasoning, code generation, and search agent tasks.

Natural Language ProcessingTransformersMultiple Languages

GLM-4.5-Air-AWQ is an 8-bit quantized version based on the GLM-4.5-Air base model, designed specifically for intelligent agents. It uses a hybrid reasoning mode, supports complex reasoning and instant response, and is released under the MIT open-source license.

Natural Language ProcessingTransformersMultiple Languages

NexaAI/Qwen3-4B is a large language model with 4 billion parameters based on the Qwen3 series. It supports seamless switching between thinking mode and non-thinking mode and performs excellently in reasoning, instruction following, intelligent agent capabilities, and multilingual support.

Natural Language ProcessingGguf

GoldDiamondGold-70b is a large language model merged from multiple pre-trained language models using the mergekit tool. This model adopts the SCE merging method, based on cogito-v2, and integrates 17 different 70B parameter-scale models, aiming to combine the advantages of each model and provide intelligent text generation and dialogue capabilities.

Natural Language ProcessingTransformers

GLM-4.5-AWQ is a 4-bit quantized version based on the GLM-4.5 base model. It uses the advanced AWQ quantization method, significantly improving inference efficiency while maintaining good performance. This model is specifically designed for intelligent agents, integrating reasoning, encoding, and intelligent agent capabilities.

Natural Language ProcessingTransformersMultiple Languages

GLM-4.5-Air-AWQ is a text generation model that performs 4-bit AWQ quantization based on the zai-org/GLM-4.5-Air base model. It is specifically designed for intelligent agent applications and performs excellently in reasoning, coding, and intelligent agent capabilities. It uses the MIT open-source license.

Natural Language ProcessingTransformersMultiple Languages

Arch-Router-1.5B is a 1.5B parameter model specifically designed for large language model routing and preference selection. It is built based on the transformers library and released under the katanemo-research license. This model can intelligently route user queries to the most suitable large language model for processing.

Natural Language ProcessingTransformersEnglish

SWE-agent-LM-7B is an open-source language model specifically designed for the software engineering field. It is fine-tuned based on Qwen2.5-Coder-7B-Instruct. This model can effectively solve software engineering-related problems and provide intelligent support for developers, which has important practical value.

Natural Language ProcessingTransformersEnglish

An image-text to text generation model based on the Transformer architecture, designed specifically for computer/GUI-related scenarios, with intelligent agent capabilities.

MultimodalGgufEnglish

Qwen3-30B-A3B-AWQ is the AWQ quantized version based on the Qwen3-30B-A3B model and is the latest generation of large language models in the Tongyi series. This model adopts the Mixture of Experts (MoE) architecture, supports the dual-mode switch between the thinking mode and the non-thinking mode, and performs excellently in reasoning, instruction following, intelligent agent capabilities, and multilingual support.

Natural Language ProcessingTransformers

Qwen3 is the latest version of the Tongyi Qianwen series of large language models, offering a complete combination of dense models and Mixture of Experts (MoE) models. Based on large-scale training, Qwen3 has achieved breakthrough progress in inference ability, instruction following, intelligent agent functions, and multilingual support.

Natural Language ProcessingTransformers

A fast image transformation technology based on latent bridge matching, specifically designed for intelligent relighting

Computer VisionSafetensors