What GPU do I need to run MiniMaxAI/MiniMax-M3-MXFP8?

440.3B parameters, published in F8_E4M3. View on Hugging Face

440.3B
Parameters
F8_E4M3
Native precision
MiniMaxM3SparseForConditionalGeneration
Architecture
image-text-to-text
Pipeline

MiniMax-M3-MXFP8 is published by MiniMaxAI on Hugging Face, with 366,068 downloads and 55 likes to date. It's a MiniMaxM3SparseForConditionalGeneration model built for image-text-to-text, published natively in F8_E4M3.

VRAM required & cheapest live GPU fit

Required VRAM = weight size at each precision, plus a fixed overhead for KV-cache, activations, and fragmentation. Full formula and assumptions: methodology.

PrecisionWeight sizeRequired VRAMCheapest live fitGPUs neededEst. $/hr (full fit)
FP8 (native)410.0 GB492.1 GBRTX PRO 60006$8.25/hr
INT4 (quantized)205.0 GB246.0 GBRTX A60006$2.18/hr

A GPU is only matched to a row if its hardware supports that precision, and the primary recommendation is always a single-GPU fit when one exists.

INT4 requires a quantized checkpoint actually published for this model, check its Hugging Face page before relying on this row.

Cheapest way to run MiniMax-M3-MXFP8 at its published (F8_E4M3) precision: 6× RTX PRO 6000, at $1.38/hr per GPU ($8.25/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.

MiniMax-M3-MXFP8: common questions

Can MiniMax-M3-MXFP8 run on a single GPU?

No. At FP8 (native) it needs 492.1 GB of VRAM, more than a single 32 GB desktop card holds. The cheapest capable card in the live feed is a 95.0 GB RTX PRO 6000, and it takes 6 of them.

Is MiniMax-M3-MXFP8 already quantized?

Yes. It is published in FP8, one byte per parameter, so the 492.1 GB figure is already a quantized footprint rather than a full-precision one. Only INT4 goes below it, at 246.0 GB. A GPU without FP8 tensor cores cannot run it as published, which is why cards here are matched on precision support and not on VRAM alone.

How many GPUs do I need to run MiniMax-M3-MXFP8?

6 at FP8 (native). It needs 492.1 GB of VRAM and the cheapest capable live offer is a 95.0 GB RTX PRO 6000, so 6 of them come to $8.25/hr in total.

Does quantizing MiniMax-M3-MXFP8 lower the GPU bill?

Yes. At FP8 (native) the cheapest live fit is 6 RTX PRO 6000 cards at $8.25/hr. At INT4 (quantized) it drops to 6 RTX A6000 cards at $2.18/hr, provided a quantized checkpoint exists for it.

Weight-to-VRAM math, the fit rules, and how live prices are normalized: full methodology.

More MiniMax M3 models

All 4 MiniMax M3 models: VRAM and GPU requirements

Related reading: RTX PRO 6000 pricing and specs, The NVIDIA Inception program, explained, Google Colab alternatives for dedicated GPU access, Free GPU credits for students and researchers, and RunPod volume disk vs. network volume, compared.

Submit the job. Everything after that is ours.

Sign up in 60 seconds. Pay for the GPU minutes you actually use.

© 2026 Aquanode. All rights reserved.

All trademarks, logos and brand names are the property of their respective owners.