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MiniMaxMoE

MiniMax-M3 (428B MoE) RAM Calculator

For MiniMax-M3 (428B MoE), plan about 256GB system RAM at Q4_K_M / 8K context — MoE still loads ~428B total weights even though only 23B active/token run per token. MiniMax-M3 (428B MoE) weights are available for local runtimes (llama.cpp / Ollama / vLLM class stacks) — buy kits you can fill with dual-channel DDR5 (or ECC RDIMM on true workstations).

Native multimodal MiniMax MoE: ~428B total / ~23B active, 1M context, MiniMax Sparse Attention (MSA). Open weights on Hugging Face.

Specs verified from official source (2026-07-17). RAM estimates use GGUF-style Q4/Q8/FP16 math; native FP4/FP8 footprints can differ.

Standard Recommendation

256GB RAM

Calculated for 4-bit (Q4_K_M) @ 8K Context

1. Workload

Inference sizes run-time memory. Training adds optimizer/activation headroom and steers toward ECC.

2. Hardware path

CPU + RAM offload path: full model weights reside in system RAM (llama.cpp / similar). Dual-channel DDR5 bandwidth is the speed bottleneck.

3. Quantization

GGUF-style bit widths for planning. Native FP4/FP8 trainer footprints can differ.

4. Context length

Grows KV cache (inference) or activation scratch (training ballpark).

8,192 tokens
VRAM Hardware Sizing · Enterprise GPU Node / Mac Studio 192GB

Recommended GPUs for MiniMax-M3 (428B MoE)

252.8 GB VRAM Required

Server-scale deployment. Running this model locally requires extreme unified memory Apple systems or professional multi-GPU servers.

Ultimate Single-GPU Flagship$1799.99

ASUS ROG Strix GeForce RTX 4090 24GB GDDR6X Flagship

VRAM: 24GB GDDR6X
Bus Width: 384-bit
Bandwidth: 1008 GB/s
Cores: 16,384 CUDA

Technical Hardware Note: Breaks 1 TB/s memory bandwidth (1,008 GB/s) with 512 Tensor Cores, generating 15-30+ tokens/sec on 70B quantized models.

Check Price & Availability on Amazon →
Undisputed $/VRAM Value King$749.99

GeForce RTX 3090 24GB GDDR6X (High-VRAM Workhorse)

VRAM: 24GB GDDR6X
Bus Width: 384-bit
Bandwidth: 936 GB/s
Cores: 10,496 CUDA

Technical Hardware Note: Features a massive 384-bit bus delivering 936 GB/s memory bandwidth. The undisputed best value per GB of VRAM for running local 32B-70B models.

Check Price & Availability on Amazon →
💡
Technical Hardware Note: Extreme parameter models require clustered multi-GPU nodes or Mac Studio 192GB Unified Memory setups to avoid out-of-memory (OOM) crashes.

Inference bandwidth snapshot

DDR4 ~45 GB/s

0.5 t/s

DDR5 ~96 GB/s

1.0 t/s

Unified ~300 GB/s

3.0 t/s

VRAM ~1008 GB/s

5.0 t/s

MiniMax-M3 (428B MoE) Quantization Comparison Matrix

Side-by-side RAM, VRAM, and GPU requirements across 4-bit, 8-bit, and 16-bit precision (at 8K context).

QuantizationWeight SizeTarget RAMVRAM ClassRecommended Hardware
4-bit (Medium)Active240.8 GB256 GB Kit252.8 GBApple Mac Studio (192GB Unified Memory) or Institutional Node (8x H100 / A100)
8-bit (High)454.8 GB512 GB Kit466.8 GBApple Mac Studio (192GB Unified Memory) or Institutional Node (8x H100 / A100)
16-bit (Lossless)856 GB1024 GB Kit868 GBApple Mac Studio (192GB Unified Memory) or Institutional Node (8x H100 / A100)
Local AI Deployment Quickstart

Run MiniMax-M3 (428B MoE) via Terminal (Ollama / vLLM)

🤗 Hugging Face Card →
Ollama CLI (Local Run):
ollama run minimax-m3
vLLM OpenAI Server (GPU Offload):
python3 -m vllm.entrypoints.openai.api_server --model MiniMaxAI/MiniMax-M3 --gpu-memory-utilization 0.95
Host RAM target

256GB

Inference · CPU offload · Q4 K_M

Model weights:240.8 GB
KV cache:0.06 GB
OS / runtime:8 GB
Host total:248.9 GB

Kit picks (256GB)

Disclosure: As an Amazon Associate I earn from qualifying purchases. Rankings use price and spec data only — not paid placement. How we rank products

A-Tech 256GB Kit (8x32GB) DDR4 2666MHz PC4-21300 ECC RDIMM 2Rx4 Dual Rank 1.2V ECC Registered DIMM 288-Pin Server & Workstation RAM Memory Upgrade Modules (A-Tech Enterprise Series)

Registered ECC
$1553.92$6.07/GBIn stock

Registered ECC usually needs a workstation/server board — not typical AM5/LGA consumer boards.

Confirm motherboard QVL / max capacity per slot before buying.

A-Tech 256GB Kit (8x32GB) DDR4 2133MHz PC4-17000 ECC RDIMM 2Rx4 Dual Rank 1.2V ECC Registered DIMM 288-Pin Server & Workstation RAM Memory Upgrade Modules (A-Tech Enterprise Series)

Registered ECC
$1388.75$5.42/GBIn stock

Registered ECC usually needs a workstation/server board — not typical AM5/LGA consumer boards.

Confirm motherboard QVL / max capacity per slot before buying.

A-Tech 256GB Kit (8x32GB) DDR4 2400MHz PC4-19200 ECC RDIMM 2Rx4 Dual Rank 1.2V ECC Registered DIMM 288-Pin Server & Workstation RAM Memory Upgrade Modules (A-Tech Enterprise Series)

Registered ECC
$1527.86$5.97/GBIn stock

Registered ECC usually needs a workstation/server board — not typical AM5/LGA consumer boards.

Confirm motherboard QVL / max capacity per slot before buying.

NEMIX RAM 256GB (8X32GB) DDR4 2933MHz PC4-23400 2Rx4 1.2V CL21 288-PIN ECC RDIMM Registered Server Memory KIT

Registered ECC
$2657.49$10.38/GBIn stock

Registered ECC usually needs a workstation/server board — not typical AM5/LGA consumer boards.

Confirm motherboard QVL / max capacity per slot before buying.

NEMIX RAM 256GB (8X32GB) DDR4 2666MHz PC4-21300 2Rx8 1.2V CL19 288-PIN ECC Unbuffered UDIMM Memory KIT

UDIMMECC
$2284.49$8.92/GBIn stock

Confirm motherboard QVL / max capacity per slot before buying.

Timetec Hynix IC DDR4 Registered ECC 1.2V 288 Pin RDIMM Server Memory RAM Module Upgrade (DDR4 2666MHz, 256GB KIT(8x32GB))

Registered ECC
$1672.99$6.54/GBIn stock

Registered ECC usually needs a workstation/server board — not typical AM5/LGA consumer boards.

Confirm motherboard QVL / max capacity per slot before buying.

NEMIX RAM 256GB (4X64GB) DDR4 3200MHz PC4-25600 2Rx4 1.2V CL22 288-PIN ECC RDIMM Registered Server Memory KIT

Registered ECC4-stick kit
$2356.99$9.21/GBIn stock

Registered ECC usually needs a workstation/server board — not typical AM5/LGA consumer boards.

Confirm motherboard QVL / max capacity per slot before buying.

Why MiniMax-M3 (428B MoE) pressures system RAM

MiniMax-M3 (428B MoE) is Mixture-of-Experts: inference activates 23B active/token, but VRAM/RAM must usually hold the full ~428B expert set for fast routing. At Q4 the weight slab is ~240.8GB before KV (~0.06GB at 8K) and ~8GB OS/runtime overhead — totaling ~248.9GB raw, rounded to a 256GB kit. Stretching toward the full 1M-token window multiplies KV far faster than weights; that is the usual “I bought enough RAM for the model but still OOM” failure on MiniMax MoE pages.

What RAM kit to buy

Shop 256GB-class capacity for MiniMax-M3 (428B MoE): workstation DDR5 RDIMM/LRDIMM or multi-kit desktop builds, not a single gamer 2×16GB stick. Use our 128GB+ price hubs and RAM Finder; confirm ECC needs for your board. GPU path: Apple Mac Studio (192GB Unified Memory) or Institutional Node (8x H100 / A100) (252.8GB VRAM class) if you want weights on-device instead of system-RAM offload.

Workload notes

For MiniMax's MiniMax-M3 (428B MoE), treat published parameter counts as the weight floor and add OS + KV + runtime overhead before shopping kits. At 428B total parameters this is frontier-scale — expect multi-GPU or heavy CPU offload even in Q4; the 256GB kit is a host-memory floor, not a promise of interactive tokens/s. Release window noted as June 2026; always re-check the official source before buying hardware for a specific checkpoint.

Technical Specifications

Total Parameter Count428 Billion
Active Parameters Per Token23 Billion
Maximum Context Window1 Million tokens
Primary Framework SupportOllama, llama.cpp, ExLlamaV2, vLLM

GPU & VRAM Sizing Profile

Enterprise GPU Node / Mac Studio 192GB
Est. VRAM Required252.8 GB VRAM
Target GPU HardwareApple Mac Studio (192GB Unified Memory) or Institutional Node (8x H100 / A100)

Hardware Profile: Server-scale deployment. Running this model locally requires extreme unified memory Apple systems or professional multi-GPU servers.

MiniMax-M3 (428B MoE) Memory FAQs

How much RAM for MiniMax-M3 (428B MoE) at Q4 vs FP16?

At Q4_K_M with an 8K context we estimate ~256GB system kits for MiniMax-M3 (428B MoE) (weights ~240.8GB). FP16 jumps to roughly a 1024GB kit class and often wants 252.8GB-class VRAM instead of host RAM alone — use the on-page calculator to retarget context and quant.

Does MoE mean I only need RAM for 23B active params on MiniMax-M3 (428B MoE)?

No. MiniMax-M3 (428B MoE) still stages ~428B total expert weights for fast routing even though only 23B active/token compute each token. Size RAM/VRAM from total parameters (and KV), not active-only marketing figures.

What GPU tier fits MiniMax-M3 (428B MoE)?

Enterprise GPU Node / Mac Studio 192GB: target about 252.8GB VRAM (Apple Mac Studio (192GB Unified Memory) or Institutional Node (8x H100 / A100)). Server-scale deployment. Running this model locally requires extreme unified memory Apple systems or professional multi-GPU servers.

Can I run MiniMax-M3 (428B MoE) with less than 256GB if I lower context?

Yes — shorter context shrinks KV (~0.06GB at 8K). Dropping to 2K–4K context can fit smaller kits, but keep OS headroom; paging kills tokens/s more than a slightly larger kit costs.

Same VRAM tier

Models that land in the same hardware profile (Enterprise GPU Node / Mac Studio 192GB) at Q4 / 8K context.