inclusionAI Releases Duo-1.0-distill Four-Step Distilled Weights
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inclusionAI released Duo-1.0-distill, four-step distilled Realization weights for Duo 1.0, its full-duplex multimodal world model for real-time audio-visual interaction. The weights are published as a PyTorch Distributed Checkpoint overlay on the inclusionAI/Duo-1.0-causal-base bundle, which supplies the shared Intent, codecs, speech models and Realization backbone; users must download that full bundle and place the weights in the same directory. The release uses an Euler sampler with 4 steps and flow shift 5.0. A companion FP8-quantized version, Duo-1.0-distill-quant, is also available; its runtime must support the packaged ModelOpt FP8 format or an equivalent conversion path. According to inclusionAI, both sets of weights were initialized from MiniMax H3 and then trained by the Duo team.
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- inclusionAI ModelsinclusionAI Releases Duo-1.0-distill Four-Step Distilled Weights for Duo 1.0
inclusionAI has released Duo-1.0-distill, the four-step distilled Realization weights for Duo 1.0, a full-duplex multimodal world model for real-time audio-visual interaction. The weights ship as a PyTorch Distributed Checkpoint overlay on the inclusionAI/Duo-1.0-causal-base bundle, using an Euler sampler with 4 steps and flow shift 5.0. The weights were initialized from MiniMax H3 and then trained by the Duo team.
- inclusionAI ModelsinclusionAI Releases Duo-1.0-distill-quant FP8 Weights for Full-Duplex Interaction
inclusionAI released Duo-1.0-distill-quant, FP8-quantized four-step distilled Realization weights for the Duo 1.0 full-duplex multimodal world model. The weights overlay onto the inclusionAI/Duo-1.0-causal-base bundle, which supplies the shared Intent, codecs, speech models and Realization backbone, and require a runtime supporting the packaged ModelOpt FP8 format. The weights were initialized from MiniMax H3 and then trained by the Duo team.
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