Omni Model Inference: How We Move Tensors Between Stages | LinkedIn

A friend once asked me: what's the fundamental difference between serving Omni multimodal models and serving plain LLMs? I thought about it and the simplest way to put it is this — a regular LLM handles a request with a single model in a single process; an Omni model handles a request by relaying it

A friend once asked me: what's the fundamental difference between serving Omni multimodal models and serving plain LLMs? I thought about it and the simplest way to put it is this — a regular LLM handles a request with a single model in a single process; an Omni model handles a request by relaying it across multiple models. Take Qwen3 Omni as an example. The lifecycle of a voice conversation request looks roughly like this: the user sends an audio clip, which first passes through an audio encoder that converts the waveform into embeddings, then feeds into the Thinker (a large language model) fo

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