MiniMax-M2-REAP-139B-A10B-IQ2_XXS-GGUF

MiniMax-M2-REAP-139B-A10B — IQ2_XXS GGUF

An IQ2_XXS quantization of cerebras/MiniMax-M2-REAP-139B-A10B, which is itself an expert-pruned (REAP) compression of MiniMax-M2 from 230B down to 139B.

So this is a compression on top of a compression: 230B → 139B by expert pruning → ~31 GB at about 2.06 bits per weight.

What is and isn't verified

Verified: loads under llama.cpp and generates — prompt processing and token generation both exercised, exit code 0.

Not measured: no KLD or perplexity table. Two lossy steps stack here — REAP expert pruning upstream, then a very aggressive 2-bit quantization — and this repo quantifies neither. That is a real caveat, not boilerplate: at IQ2_XXS on an already-pruned model you should expect noticeable degradation and should evaluate it on your own task before trusting it.

For a release where fidelity is measured against the unquantized reference, see Qwen3.6-27B-GGUF.

Run it

llama-cli -m cerebras_MiniMax-M2-REAP-139B-A10B-IQ2_XXS.gguf -c 32768 -no-cnv -p "your prompt"

Credit & license

• Pruned model © Cerebras — MiniMax-M2-REAP-139B-A10B
• Base model © MiniMax AI — MiniMax-M2

Distributed under the modified MIT license of the upstream models: MIT terms, with the added condition that commercial products above 100M monthly active users or $30M annual recurring revenue must display "MiniMax M2" in their interface. This repo adds only the quantization.