What GPU do I need to run MiniMaxAI/MiniMax-M2?
228.7B parameters, published in F8_E4M3. View on Hugging Face
MiniMax-M2 is published by MiniMaxAI on Hugging Face, with 234,903 downloads and 1,503 likes to date. It's a MiniMaxM2ForCausalLM model built for text-generation, 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.
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 caveat: requires a quantized checkpoint actually published for this model — check its Hugging Face page before relying on this row.
Cheapest way to run MiniMax-M2 at its published (F8_E4M3) precision: 3× RTX PRO 6000 WS on vastai, at $1.16/hr per GPU ($3.48/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.
Weight-to-VRAM math, the fit rules, and how live prices are normalized: full methodology.
More MiniMaxAI models
- MiniMax-H3 (33.1B, BF16)
- MiniMax-M2.7 (228.7B, F8_E4M3)
- MiniMax-M2.5 (228.7B, F8_E4M3)
- Qwen3-0.6B (752M, BF16)
- Qwen3-8B (8.2B, BF16)
- gpt2 (137M, F32)
