Running MiniMax M3 on RTX PRO 6000 server
MiniMax M3 has 428 billion parameters. RTX PRO 6000 server offers 768 GB of GDDR7 across 8 GPUs memory. This page puts the two side by side.
How much memory does MiniMax M3 need?
Weights take the parameter count multiplied by the format size, plus a 15% runtime margin for activations and buffers. The attention cache sits on top: it grows with context length and with the number of concurrent requests, so it is sized case by case.
| Format | Weights in memory | On this machine | What the format costs |
|---|---|---|---|
| FP16 | 984 GB | does not fit | full precision, the quality reference |
| FP8 | 492 GB | fits | negligible loss on most tasks |
| NVFP4 | 246 GB | fits | Blackwell format, native FP4 compute |
| Q4 | 246 GB | fits | block quantisation, broadly supported |
MiniMax M3 activates 23 billion parameters per token out of 428 billion. Active parameters govern speed, not footprint: every expert stays resident in memory. Confusing the two under-sizes the machine by an order of magnitude.
What is left to serve requests?
MiniMax M3 fits comfortably on RTX PRO 6000 server. In FP8, its weights take about 492 GB of the 768 GB available, leaving 276 GB for the attention cache and concurrency. The remaining margin decides how many concurrent requests and how much context the machine sustains. A margin below a quarter of memory forces a limit on context or on concurrency.
RTX PRO 6000 server ranges from 250 to 350 k€, indicative and not contractual. The machine targets the PME, GE segment.
Where else can MiniMax M3 run?
- MiniMax M3 on Mac Studio Ultra
- MiniMax M3 on DGX Station
- MiniMax M3 on H200 SXM server
- MiniMax M3 on B200 SXM
- MiniMax M3 on B300 SXM
See the MiniMax M3 and RTX PRO 6000 server fact sheets.
How much memory does MiniMax M3 need?
In FP8, weights take about 492 GB including the runtime margin. The attention cache sits on top and depends on context.
Does MiniMax M3 fit on RTX PRO 6000 server?
MiniMax M3 fits comfortably on RTX PRO 6000 server. In FP8, its weights take about 492 GB of the 768 GB available, leaving 276 GB for the attention cache and concurrency.
Method
Parameter counts and memory figures come from the site fact sheets. Memory footprints are calculated, not measured: a reading on real hardware may differ depending on the engine and the exact weight format. Prices are indicative and not contractual.