MiniMax-M2.5-REAP-139B-A10B-GGUF – AI Model by BennyDaBall | AlphaNeural AI

You can deploy this model and start earning money today!

BennyDaBall/
MiniMax-M2.5-REAP-139B-A10B-GGUF

like

0

text-generation

tomngdev/MiniMax-M2.5-REAP-139B-A10B-GGUF

endpoints_compatible

Views

No views yet

MiniMax-M2.5-REAP-139B-A10B-GGUF

Follow me on X @BennyDaBall_OG !

This is the REAP model in practical pants: high quality GGUF quants for local inference without setting your workstation on fire.

Built from:

Base: MiniMaxAI/MiniMax-M2.5
REAP source: tomngdev/MiniMax-M2.5-REAP-139B-A10B-GGUF (BF16 split)
Quantized locally with llama.cpp on Strix Halo + high RAM mode.

Available Quants

Quant	Status	Size (GiB)	Notes
`Q8_0`	uploaded	137.78	Highest quality quant in this pack
`Q5_K_M`	uploading	92.33	Better quality/size balance
`Q4_K_M`	uploaded	78.83	Strong practical default

File Layout

All quants are split GGUF sets (00001-of-00007 etc.) for safer handling of very large models.

Quality Notes

These are generated from BF16 REAP GGUF, not requantized from lower precision.
Token embedding and output tensors are kept at Q8_0 during quantization for quality retention.

Usage

Use any first shard with llama.cpp; it auto-discovers sibling shards:

llama-cli -m MiniMax-M2.5-REAP-Q4_K_M-00001-of-00007.gguf -ngl 0 -c 8192

Credits

MiniMaxAI for MiniMax-M2.5
tomngdev for the BF16 REAP GGUF release
BennyDaBall for this quant pack

Disclaimer

You are responsible for your own use, outputs, and compliance with applicable laws and platform policies.

Follow me on X @BennyDaBall_OG !