# Mixture of Experts Model

Qwen3 is the latest generation of large language models in the Tongyi Qianwen series, offering a complete suite of dense models and Mixture of Experts (MoE) models. Based on large-scale training, Qwen3 has achieved breakthrough progress in reasoning capabilities, instruction following, agent functionalities, and multilingual support.

Qwen3 is the latest generation of large language models in the Tongyi Qianwen series, offering a complete combination of dense models and Mixture of Experts (MoE) models. Based on large-scale training, Qwen3 achieves breakthrough progress in reasoning capabilities, instruction following, agent functions, and multilingual support.

Qwen3 is the latest generation of large language models in the Qwen series, offering a range of dense and Mixture of Experts (MoE) models. Based on extensive training, Qwen3 has achieved groundbreaking progress in reasoning, instruction following, agent capabilities, and multilingual support.

Qwen3-30B-A3B-Base is the latest 30.5B parameter-scale Mixture of Experts (MoE) large language model in the Qwen series, supporting 119 languages and 32k context length.

A Mixture of Experts model designed to serve as the soul of AI virtual anchors, combining code generation, instruction following, and multi-turn dialogue capabilities

An experimental role-playing-oriented Mixture of Experts model, aiming to achieve performance in role-playing/emotional role-playing tasks that is comparable to or better than Mixtral 8x7B and its fine-tuned versions.

Snowflake Arctic is a large language model developed by Snowflake AI Research Team, featuring a dense Mixture of Experts (MoE) architecture with 480 billion parameters, specifically designed for efficient text and code generation.

J.O.S.I.E.3-Beta12-7B-slerp is a 7B-parameter large language model created by merging Weyaxi/Einstein-v6-7B and argilla/CapybaraHermes-2.5-Mistral-7B models, supporting multilingual interaction and adopting the ChatML prompt format.

Arctic is a dense Mixture of Experts (MoE) architecture large language model developed by the Snowflake AI Research team, with 480 billion parameters, open-sourced under the Apache-2.0 license.

Mixtral-8x22B-Instruct-v0.1 is a large language model fine-tuned for instructions based on Mixtral-8x22B-v0.1, supporting multiple languages and function calling capabilities.

A 141-billion parameter Mixture of Experts (MoE) model fine-tuned from Mixtral-8x22B-v0.1, with 35 billion active parameters, primarily designed for English text generation tasks

A medium-scale Mixture of Experts (MoE) implementation based on Dolphin-2.6-Mistral-7B-DPO-Laser, with an average performance improvement of approximately 1 point in evaluations

phixtral-2x2_8 is the first Mixture of Experts (MoE) model built upon two microsoft/phi-2 models, outperforming each individual expert model.