inclusionAI Releases Ming-3.0-audio-flash, a 126B Native Audio MoE Model
InclusionAI has released Ming-3.0-audio-flash, a 126B parameter native audio-language Mixture-of-Experts model. It accepts audio and text inputs to support complex speech recognition, long-audio understanding, audio reasoning, and synthesized speech outputs in Chinese and English. This release provides the open-source community with a large-scale, powerful native audio model capable of multidimensional perception and reasoning. It enhances local AI capabilities for complex speech and acoustic tasks across both Chinese and English environments. Ming-3.0-audio-flash features 126B total parameters with only 6.5B activated per inference step, operating under an MIT license. It handles noisy environments, multi-speaker recordings, dialects, non-speech sounds, and music alongside optional voice synthesis.
## BACKGROUND
A native audio-language model is designed to process and reason directly with audio signals rather than relying solely on traditional text transcriptions. Mixture-of-Experts (MoE) is an architecture that scales model capacity massively while keeping computational overhead low by routing tokens to only a small subset of expert subnetworks during each inference step.