MiniMaxAI·MiniMaxM2ForCausalLM

MiniMax M2.5 — Hardware Requirements & GPU Compatibility

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MiniMax M2.5 is a large-scale mixture-of-experts model from MiniMax, a well-funded Chinese AI company. With roughly 228 billion total parameters and a MoE architecture that activates only a fraction per token, it aims to deliver performance competitive with much larger dense models while keeping inference costs manageable. Running it locally requires substantial hardware due to its large parameter footprint, but quantized versions can make it accessible to users with multi-GPU setups looking for a powerful multilingual model with strong Chinese and English capabilities.

520.4K downloads 1.2K likesMar 2026197K context

Specifications

Publisher
MiniMaxAI
Parameters
228.7B
Architecture
MiniMaxM2ForCausalLM
Context Length
196,608 tokens
Vocabulary Size
200,064
Release Date
2026-03-10
License
Other

Get Started

How Much VRAM Does MiniMax M2.5 Need?

Select a quantization to see compatible GPUs below.

QuantizationBitsVRAM
IQ2_XXS2.2063.5 GB
IQ2_M2.7077.8 GB
IQ3_XXS3.1089.2 GB
Q2_K3.4097.8 GB
Q3_K_S3.50100.6 GB
Q3_K_M3.90112.0 GB
Q4_04.00114.9 GB
IQ4_XS4.30123.5 GB
Q4_14.50129.2 GB
Q4_K_S4.50129.2 GB
IQ4_NL4.50129.2 GB
Q4_K_M4.80137.8 GB
Q5_K_S5.50157.8 GB
Q5_K_M5.70163.5 GB
Q6_K6.60189.2 GB
Q8_08.00229.3 GB

Which GPUs Can Run MiniMax M2.5?

Q4_K_M · 137.8 GB

MiniMax M2.5 (Q4_K_M) requires 137.8 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 180+ GB is recommended. Using the full 197K context window can add up to 24.7 GB, bringing total usage to 162.5 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.

Which Devices Can Run MiniMax M2.5?

Q4_K_M · 137.8 GB

4 devices with unified memory can run MiniMax M2.5, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Pro M2 Ultra (192 GB).

Related Models

Frequently Asked Questions

How much VRAM does MiniMax M2.5 need?

MiniMax M2.5 requires 137.8 GB of VRAM at Q4_K_M, or 229.3 GB at Q8_0. Full 197K context adds up to 24.7 GB (162.5 GB total).

VRAM = Weights + KV Cache + Overhead

Weights = 228.7B × 4.8 bits ÷ 8 = 137.2 GB

KV Cache + Overhead 0.6 GB (at 2K context + ~0.3 GB framework)

KV Cache + Overhead 25.3 GB (at full 197K context)

VRAM usage by quantization

137.8 GB
162.5 GB

Learn more about VRAM estimation →

Can NVIDIA GeForce RTX 5090 run MiniMax M2.5?

No — MiniMax M2.5 requires at least 63.5 GB at IQ2_XXS, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.

What's the best quantization for MiniMax M2.5?

For MiniMax M2.5, Q4_K_M (137.8 GB) offers the best balance of quality and VRAM usage. Q5_K_S (157.8 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 63.5 GB.

VRAM requirement by quantization

IQ2_XXS
63.5 GB
Q3_K_S
100.6 GB
Q4_1
129.2 GB
Q4_K_M
137.8 GB
Q5_K_S
157.8 GB
Q8_0
229.3 GB

★ Recommended — best balance of quality and VRAM usage.

Learn more about quantization →

Can I run MiniMax M2.5 on a Mac?

MiniMax M2.5 requires at least 63.5 GB at IQ2_XXS, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.

Can I run MiniMax M2.5 locally?

Yes — MiniMax M2.5 can run locally on consumer hardware. At Q4_K_M quantization it needs 137.8 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.

How fast is MiniMax M2.5?

At Q4_K_M, MiniMax M2.5 can reach ~21 tok/s on AMD Instinct MI300X. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.

tok/s = (bandwidth GB/s ÷ model GB) × efficiency

Example: AMD Instinct MI300X5300 ÷ 137.8 × 0.55 = ~21 tok/s

Estimated speed at Q4_K_M (137.8 GB)

~21 tok/s

Real-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.

Learn more about tok/s estimation →

What's the download size of MiniMax M2.5?

At Q4_K_M, the download is about 137.22 GB. The full-precision Q8_0 version is 228.70 GB. The smallest option (IQ2_XXS) is 62.89 GB.