MiniMax M3 — MXFP4 (mixed precision) A 4 bit MXFP4 quantization of MiniMax M3, produced with qstream . The routed MoE experts (≈95% of the weights) are quantized to MXFP4; everything that is quality sensitive is kept at higher precision. 4x RTX PRO 6000 launch recipe by 0xSero: https://github.com/0xSero/minimax m3 sm120 Size 237 GB (down from 444 GB MXFP8 source, ~53%) Format compressed tensors mixed precision (E2M1 4 bit + E8M0 group 32 scales) Base MiniMax M3 (256K context vision language sparse MoE, 128 experts top 4 + 1 shared, SwiGLU OAI, lightning indexer block sparse attention) What is quantized to what Component Precision Why Routed experts ( block sparse moe.experts. ) MXFP4 (4 bit) 95% of the weights — the only place worth the size win Shared expert, attention, dense MLP MXFP8 (8 bit, native passthrough) runs on every token / sensitive — kept lossless from the source Embeddings, lm head, router gate, vision tower, projector, norms BF16 / F32 unchanged Quality (this checkpoint, served on vLLM) Metric Result Perplexity (clean English) 5.32 GSM8K (full 1319 problem test set, chain of thought) 92.9% (1225/1319) Quantization is faithful: a degraded checkpoint would show PPL in…
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