MiniMax·MiniMax·MiniMaxM3SparseForConditionalGeneration

MiniMax M3 — Hardware Requirements & GPU Compatibility

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MiniMax M3 is a 427.0B-parameter open language model from MiniMax in the MiniMax family. It supports a context window of up to 1,048,576 tokens. At Q4_K_M it needs about 256.71 GB of VRAM — see which GPUs and Macs can run it below.

189.0K downloads 1.3K likes 408.7K quant downloads1049K context

Specifications

Publisher
MiniMax
Family
MiniMax
Parameters
427.0B
Architecture
MiniMaxM3SparseForConditionalGeneration
Context Length
1,048,576 tokens
Vocabulary Size
200,064
Release Date
2026-06-02
License
Other

Get Started

How Much VRAM Does MiniMax M3 Need?

Select a quantization to see compatible GPUs below.

QuantizationBitsVRAM
Q2_K3.40182.0 GB
Q3_K_M3.90208.7 GB
Q4_K_M4.80256.7 GB
Q5_K_M5.70304.8 GB
Q6_K6.60352.8 GB
Q8_08.00427.5 GB

Which GPUs Can Run MiniMax M3?

Q4_K_M · 256.7 GB

MiniMax M3 (Q4_K_M) requires 256.7 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 334+ GB is recommended. Using the full 1049K context window can add up to 96.5 GB, bringing total usage to 353.2 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.

Which Devices Can Run MiniMax M3?

Q4_K_M · 256.7 GB

3 devices with unified memory can run MiniMax M3, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio (M3 Ultra, 512GB).

Decent

Enough memory, may be tight

Where to Download MiniMax M3

Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.

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Frequently Asked Questions

How much VRAM does MiniMax M3 need?

MiniMax M3 requires 256.7 GB of VRAM at Q4_K_M, or 854.6 GB at BF16. Full 1049K context adds up to 96.5 GB (353.2 GB total).

VRAM = Weights + KV Cache + Overhead

Weights = 427.0B × 4.8 bits ÷ 8 = 256.2 GB

KV Cache + Overhead 0.5 GB (at 2K context + ~0.3 GB framework)

KV Cache + Overhead 97 GB (at full 1049K context)

VRAM usage by quantization

256.7 GB
353.2 GB

Learn more about VRAM estimation →

Can NVIDIA GeForce RTX 5090 run MiniMax M3?

No — MiniMax M3 requires at least 117.9 GB at IQ2_XXS, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.

What's the best quantization for MiniMax M3?

For MiniMax M3, Q4_K_M (256.7 GB) offers the best balance of quality and VRAM usage. Q5_K_S (294.1 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 117.9 GB.

VRAM requirement by quantization

IQ2_XXS
117.9 GB
IQ3_S
182.0 GB
IQ4_NL
240.7 GB
Q4_K_M
256.7 GB
Q5_K_M
304.8 GB
BF16
854.6 GB

★ Recommended — best balance of quality and VRAM usage.

Learn more about quantization →

Can I run MiniMax M3 on a Mac?

MiniMax M3 requires at least 117.9 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 M3 locally?

Yes — MiniMax M3 can run locally on consumer hardware. At Q4_K_M quantization it needs 256.7 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.

How fast is MiniMax M3?

At Q4_K_M, MiniMax M3 can reach ~17 tok/s on AMD Instinct MI350X. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.

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

Example: NVIDIA B3008000 ÷ 256.7 × 0.65 = ~20 tok/s

Estimated speed at Q4_K_M (256.7 GB)

~20 tok/s
~17 tok/s
~17 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 M3?

At Q4_K_M, the download is about 256.22 GB. The full-precision BF16 version is 854.08 GB. The smallest option (IQ2_XXS) is 117.44 GB.

Which GPUs can run MiniMax M3?

No single consumer GPU has enough VRAM to run MiniMax M3 at Q4_K_M (256.7 GB). Multi-GPU or professional hardware is required.

Which devices can run MiniMax M3?

3 devices with unified memory can run MiniMax M3 at Q4_K_M (256.7 GB), including Mac Studio (M3 Ultra, 512GB), NVIDIA DGX A100 640GB, NVIDIA DGX H100. Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.