Qwen3.5-Omni - A multimodal large model launched by Ali Tongyi

What is Qwen3.5-Omni?

Qwen3.5-Omni is a multimodal large-scale model launched by Alibaba Tongyi Lab, capable of simultaneously understanding text, images, audio, and audio/video input. The model employs a Thinker-Talker collaborative architecture and Hybrid-MoE technology, achieving state-of-the-art (SOTA) performance in 215 audio/audio/video tasks, surpassing Gemini-3.1 Pro. The model supports 256K ultra-long context, semantic segmentation, timbre cloning, and voice control. It natively integrates WebSearch and Function Call, and possesses naturally emerging Audio-Visual Vibe Coding capabilities, directly generating runnable code from audio/video instructions.

Main functions of Qwen3.5-Omni

• Full-modal understandingThe model natively and seamlessly processes text, images, audio, and video input, and supports the generation of fine-grained descriptions with timestamps.
• Video intelligent analysisThe model can generate structured video notes, recognizing video content, dialogue, camera transitions, and sensitive information.
• Vibe CodingIt has the ability to generate code naturally based on audio and video instructions without requiring special training.
• Real-life dialogueIt supports semantic interruption and voice control, can distinguish between environmental noise and real interruptions, and adjusts the emotional speech rate in real time.
• Timbre CloningUpload your recordings to customize your own AI voice tone, which supports natural generation of multiple languages.
• Intelligent task executionIt natively integrates WebSearch and Function Call, allowing it to autonomously determine and invoke tools to complete complex tasks.

The technical principle of Qwen3.5-Omni

• Thinker-Talker Division of Labor ArchitectureThinker is responsible for multimodal understanding, receiving visual and audio signals and encoding location information through TMRoPE; Talker is responsible for speech generation, using RVQ encoding based on Thinker output to achieve efficient speech synthesis. The two work together to separate understanding and generation.
• Hybrid-Attention MoE:By assigning tasks such as listening, seeing, and understanding to different expert networks, intermodal interference is avoided, and 215 state-of-the-art (SOTA) performance metrics are achieved while maintaining text visual capabilities.
• ARIA Dynamic Alignment TechnologyThe model adaptively adjusts the rates of text and speech units, solving the problems of missing words and unclear pronunciation of numbers caused by the traditional fixed ratio, and supports real-time voice control response.

How to use Qwen3.5-Omni

• API calls:accessAlibaba Cloud Hundred RefinementsSearching for Qwen3.5-Omni on the official website allows you to access the API. It offers three sizes: Plus, Flash, and Light, to meet the performance and cost requirements of different scenarios.
• Online experience: directly in Qwen Chat Experience the full capabilities of Qwen3.5-Omni; get started quickly without deployment.

Key information and usage requirements for Qwen3.5-Omni

• PublisherAlibaba Tongyi Lab
• Model localizationFull-modal large model (text/image/audio/video)
• Version SpecificationsAvailable in Plus, Flash, and Light sizes.
• Performance215 state-of-the-art features, surpassing the Gemini-3.1 Pro in every aspect.
• Context length256K (Supports 10 hours of audio / 1 hour of video)
• Language support74 speech recognition languages + 39 dialects
• Core ArchitectureThinker-Talker Division of Labor + Hybrid-MoE

Qwen3.5-Omni's core advantages

• Full-modal native unificationIt truly and seamlessly understands text, images, audio, and video.
• Top performanceIt tops the charts in 215 SOTA categories, and its audio/video capabilities surpass those of the Gemini-3.1 Pro in all aspects.
• Extremely long context256K context length, supports 10 hours of audio or 1 hour of video processing.
• Natural InteractionIt supports semantic interruption, voice control, and voice cloning, providing a conversational experience close to that of a real person.
• Emergent capabilitiesIt possesses Audio-Visual Vibe Coding capabilities without specific training, enabling it to generate code based on audio and video.
• Intelligent ExecutionNative support for WebSearch and Function Calls, seamlessly connecting chat with tasks.
• Multilingual coverageIt supports 74 speech recognition languages and 39 dialects, breaking down language barriers.

Comparison of Qwen3.5-Omni with similar competing products

Qwen3.5-Omni Application Scenarios

• Video creation and editingIt automatically generates structured descriptions with timestamps, recognizes scenes, dialogues, and camera transitions, detects sensitive content, and converts long videos into searchable notes.
• Smart Meeting AssistantIt can transcribe meeting content in real time, distinguish speakers, generate meeting minutes, and support multilingual recognition and translation.
• Code-assisted developmentVibe Coding: Generates front-end pages or Python code directly from design drafts or verbal requirements.
• Personalized voice assistantIt clones a unique voice to create a digital clone, supports voice control of volume and mood, and provides a companion-like interaction.
• Multilingual real-time communicationThe model supports 74 languages and 39 dialects, enabling real-time cross-language dialogue and translation.
• Intelligent task executionIt combines WebSearch with tool calls to complete complex tasks such as checking the weather, booking hotels, and searching for information.