Update 4/15/26 Calibration data updated, KLD reduced by ~10%. Update 4/12/26 Calibration data updated, KLD reduced by ~20%. Note: If you're experiencing issues with spurious spaces after punctuation, try downgrading transformers to 0.4.67 Model Description MiniMax M2.7 NVFP4 is an NVFP4 quantized version of MiniMaxAI/MiniMax M2.7, a 230B parameter Mixture of Experts language model with 10B active parameters. The original model weights were converted from the official FP8 checkpoint to BF16, then quantized to NVFP4 (4 bit with blockwise FP8 scales per 16 elements) using NVIDIA Model Optimizer. What's quantized Only the MoE expert MLP layers (gate, up, and down projections) are quantized to NVFP4. All other layers are left in BF16. Since the expert weights constitute the vast majority of model parameters in an MoE architecture, this still yields significant memory savings. Calibration uses natural top k routing rather than forcing all experts to activate, so each expert's quantization scales reflect the token distributions it actually sees during inference. To compensate, calibration was run on a vastly larger number of samples than typical to ensure broad expert coverage through nat…
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