CuttyMOA-1.2

CuttyMOA-1.2

The flagship Mixture-of-Experts AI model of the CUTEADMOA ecosystem.

Overview

CuttyMOA-1.2 is a CPU-first Mixture-of-Experts language model built on the Qwen 3.6 35B A3B architecture. With only ~3B parameters active per token from a 35B expert pool, it achieves strong reasoning performance while running efficiently on CPU hardware — no GPU required.

It is the direct successor to CuttyMOA-1.0, upgraded from a 15B dense model to 35B MoE with 2.3× more total knowledge capacity.

Why CuttyMOA-1.2?

Quick Start

Option 1: llama.cpp (Recommended for VPS)

# Download the GGUF
huggingface-cli download sayeed105236/CuttyMOA-1.2 \
  CuttyMOA-1.2-Q4_K_S.gguf --local-dir ./

# Run with llama-server
./llama-server \
  -m CuttyMOA-1.2-Q4_K_S.gguf \
  -c 8192 -n 1024 \
  --port 5401 --host 127.0.0.1

# Test
curl http://127.0.0.1:5401/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{"messages":[{"role":"user","content":"Who are you?"}],"max_tokens":50}'

Option 2: Ollama

# Download GGUF + Modelfile from this repo, then:
ollama create cuttymoa-1.2 -f Modelfile
ollama run cuttymoa-1.2

Option 3: CUTEADMOA Integration

CuttyMOA-1.2 plugs directly into the CUTEADMOA Mixture-of-Agents platform as a local inference engine. See cuteadmoa.site for platform documentation.

Hardware Requirements

Runs on any x86_64 CPU. Tested on AMD EPYC, Intel Xeon, Apple M-series.

Training Data

The model ships with the CUTEADMOA Knowledge Corpus:

• 857,223 instruction-response pairs across 24 domains
• Domains: code, security, news, medical, legal, finance, science, multilingual, RAG, agentic-tools, reasoning, dialogue, and more
• Full dataset available at sayeed105236/cuttymoa-training-corpus

Future Fine-Tuning

QLoRA fine-tuning recipes will be published for users who want to adapt CuttyMOA-1.2 to their own domains. Budget ~$2-4 on RunPod A40 for a full fine-tuning run.

CUTEADMOA Ecosystem

CuttyMOA-1.2 is the local inference engine for CUTEADMOA, a Mixture-of-Agents platform combining:

• 23+ text models across 6 providers
• 24 security intents with HTML/DOCX reports
• Enterprise web scraping (ScrapePower)
• Native macOS & iOS apps
• Smart routing with multi-model aggregation

📄 Publication

This model is part of the CUTEADMOA platform presented in:

Md Abu Sayeed. CUTEADMOA: A Unified Mixture-of-Agents Platform with Continuous Self-Training for Autonomous Enterprise AI Automation. Advances in Artificial Intelligence and Robotics Research, Vol. 2, No. 3, pp. 190–208, September 2026.

• 📰 Paper page: https://www.scirp.org/journal/paperinformation?paperid=154162
• 📄 Full-text PDF: https://www.scirp.net/pdf/airr_2970152.pdf
• 🔗 DOI: https://doi.org/10.4236/airr.2026.23011

@article{sayeed2026cuteadmoa,
  author  = {Md Abu Sayeed},
  title   = {CUTEADMOA: A Unified Mixture-of-Agents Platform with Continuous Self-Training for Autonomous Enterprise AI Automation},
  journal = {Advances in Artificial Intelligence and Robotics Research},
  volume  = {2},
  number  = {3},
  pages   = {190--208},
  year    = {2026},
  issn    = {3143-3987},
  doi     = {10.4236/airr.2026.23011},
  url     = {https://www.scirp.org/journal/paperinformation?paperid=154162}
}

Version History

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