Skip to content
localllm
日本語

peasantsmith

MiniMax-M3.1-Flash-Maya

Image input

Parameters
426.2B
Max context length
1,048,576
Architecture
minimax-m3
License
Unverified
Base model
MiniMaxAI/MiniMax-M3.1-Flash
License
minimax-community
llama.cpp
b10141+

About MiniMax-M3.1-Flash-Maya

MiniMax-M3.1-Flash-Maya is a GGUF model based on MiniMaxAI/MiniMax-M3.1-Flash on Hugging Face. GGUF files are published by peasantsmith/MiniMax-M3.1-Flash-Maya-GGUF. It has about 426.2B parameters, the minimax-m3 architecture, a maximum context length of 1,048,576 tokens (values written in the GGUF).

There are 2 quantizations, with file sizes from 93.0 GB (IQ1_S) to 122 GB (IQ2_XXS) (actual sizes on Hugging Face).

Running IQ1_S (93.0 GB) with an 8,192-token context needs an estimated 95.1 GB of memory, and an estimated 98.1 GB at 32,768 tokens. For 8,192 tokens, a GPU with 96 GB or more of VRAM, or a Mac with 96 GB or more of unified memory, is a rough guide (macOS caps how much memory the GPU can use, so leave some headroom).

The original model is licensed under minimax-community. Check the original license for the terms of use.

File size and estimated memory per quantization

  • Up to 8 GB
  • Up to 16 GB
  • Up to 24 GB
  • Up to 48 GB
  • Up to 128 GB
  • More

File sizes are the actual values on Hugging Face. Memory is estimated for each context length (KV cache f16). The formula is in How memory is calculated.

All memory figures are Estimated (KV cache f16). It should run on a setup with at least this much VRAM (or Mac unified memory). Click a value to see the devices and models that fit that amount (Find by GPU / Mac).

About the "quality guide" (how far a quantization drifts from the original)

For each quantization type, how far the output drifts from the original model, grouped into six levels from values llama.cpp measured on Llama-3-8B.

The value is mean KLD (the difference between the original and quantized model in next-token probabilities); smaller means closer to the original. Quantizations made with an imatrix (importance data) come out slightly smaller. Levels use the value without an imatrix (or with one, for types that only have that).

These values were not measured on this model. Larger models and MoE models tend to drift less with the same type. Distributor-specific mixed types (such as UD-Q4_K_XL) cannot be matched by type name alone, so they show "-".

Quantization Quality guide KLD (no imatrix) KLD (imatrix) Size (Llama-3-8B)
Q8_0 Nearly identical 0.0014 - 7.96 GiB
Q6_K Very small 0.0055 - 6.14 GiB
Q5_K_M Very small 0.0108 - 5.33 GiB
Q5_K_S Small 0.0166 - 5.21 GiB
Q5_1 Small 0.0180 - 5.65 GiB
Q5_0 Small 0.0222 - 5.21 GiB
Q4_K_M Small 0.0313 0.0282 4.58 GiB
Q4_K_S Medium 0.0431 0.0320 4.37 GiB
IQ4_NL Small - 0.0357 4.35 GiB
IQ4_XS Small - 0.0363 4.14 GiB
Q4_1 Medium 0.0717 - 4.78 GiB
Q4_0 Medium 0.0719 - 4.34 GiB
Q3_K_L Medium 0.0872 0.0731 4.03 GiB
Q3_K_M Medium 0.1019 0.0844 3.74 GiB
IQ3_M Medium - 0.1025 3.53 GiB
IQ3_S Medium - 0.1113 3.42 GiB
IQ3_XS Large - 0.1387 3.28 GiB
IQ3_XXS Large - 0.1836 3.05 GiB
Q3_K_S Large 0.2282 0.1998 3.41 GiB
IQ2_M Large - 0.3260 2.74 GiB
Q2_K Very large 0.4451 0.3322 2.96 GiB
Q2_K_S Very large - 0.4034 2.96 GiB
IQ2_S Very large - 0.4392 2.56 GiB
IQ2_XS Very large - 0.5463 2.43 GiB
IQ2_XXS Very large - 0.8120 2.24 GiB
IQ1_M Very large - 1.3931 2.01 GiB
IQ1_S Very large - 2.2546 1.88 GiB

Source: llama.cpp (MIT), measured on Llama-3-8B against FP16, Wikitext-2, revision f364eb6f. Original table · Reading and choosing quantizations

GGUF source

peasantsmith/MiniMax-M3.1-Flash-Maya-GGUF

Published by the original developer About this label

Last checked: Nov 11, 2026

Architecture
minimax-m3
llama.cpp b10141 and later
Parameters
426.2B
Max context length
1,048,576
License
minimax-community Unverified
File size and memory per quantization for MiniMax-M3.1-Flash-Maya (peasantsmith/MiniMax-M3.1-Flash-Maya-GGUF)
Quantization File size Measured Quality guide 4,096 8,192 16,384 32,768 65,536 131,072 262,144 1,048,576 max
IQ1_S (2 parts) 93.0 GB Very large 94.6 GB 95.1 GB 96.1 GB 98.1 GB 102 GB 110 GB 126 GB 223 GB
IQ2_XXS (3 parts) 122 GB Very large 124 GB 125 GB 126 GB 128 GB 132 GB 140 GB 156 GB 252 GB 
Ollama  ollama run hf.co/peasantsmith/MiniMax-M3.1-Flash-Maya-GGUF:IQ1_S
llama.cpp  llama-server -hf peasantsmith/MiniMax-M3.1-Flash-Maya-GGUF:IQ1_S

License and commercial use

minimax-community Unverified

This site has not verified this license text yet. Check the original before commercial use.

Based on the license on the original model's Hugging Face page.

The summary states facts this site read from the original text and is not legal advice. Always check the original license and its latest terms before use. All licenses

How to run

Mainline llama.cpp can load this model's format (minimax-m3) from b10141 (Jul 26, 2026) onward. Ollama and LM Studio bundle llama.cpp internally, so an older app fails to load it with errors such as "unknown model architecture". If that happens, update the app.

Example commands using IQ1_S. To use another quantization, replace the name with one from the table above. How to run local LLMs

Ollama

Run it by pointing directly at the GGUF on Hugging Face.

ollama run hf.co/peasantsmith/MiniMax-M3.1-Flash-Maya-GGUF:IQ1_S

llama.cpp

Pass the repository and quantization name to llama-server (or llama-cli) with -hf.

llama-server -hf peasantsmith/MiniMax-M3.1-Flash-Maya-GGUF:IQ1_S

LM Studio

Paste peasantsmith/MiniMax-M3.1-Flash-Maya-GGUF into the search box, download it, and choose the quantization from the file list.

Frequently asked questions

How much memory do I need to run MiniMax-M3.1-Flash-Maya (IQ1_S)?
The file size is 93.0 GB (measured). With a 8,192-token context, the estimated memory including the KV cache is 95.1 GB. The formula is published at https://localllm.az-arte.com/en/guide/memory-calculation.
Can MiniMax-M3.1-Flash-Maya be used commercially?
The original model's license is minimax-community (Commercial use not verified). Check the original license text before deciding.
Does MiniMax-M3.1-Flash-Maya run in 8 GB, 12 GB, 16 GB or 24 GB of VRAM?
8 GB: no quantization fits; 12 GB: no quantization fits; 16 GB: no quantization fits; 24 GB: no quantization fits (estimated at 8,192 tokens with an f16 KV cache, files from the most-downloaded source).
What is the command to run MiniMax-M3.1-Flash-Maya with Ollama?
Run "ollama run hf.co/peasantsmith/MiniMax-M3.1-Flash-Maya-GGUF:IQ1_S" to use the GGUF on Hugging Face directly. To use another quantization, replace the name at the end.