title	MAYA AI
emoji	🧬
colorFrom	indigo
colorTo	yellow
sdk	static
pinned	true
license	apache-2.0
short_description	MAYA AI — Proto_AGI, Evolutionary LLM Merging, Leaderboards & Chat

🧬 MAYA AI — Proto_AGI & Evolutionary LLM Platform

Building the path to Proto_AGI through evolutionary model merging, open benchmarks, and conversational intelligence.

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🎯 What is MAYA AI?

MAYA AI is a research-driven AI lab pioneering the next generation of open-source language intelligence. We combine three pillars into a single mission:

Pillar	Focus	Flagship
🧬 Proto_AGI Research	Evolutionary LLM model merging (Darwin V7 lineage)	Darwin-31B-Opus / Darwin-27B-Opus
🏆 Open Benchmarks	Transparent multi-benchmark leaderboards	all-leaderboard
💬 Conversational AI	Production-grade chat & voice interfaces	QWEN-3_5-CHAT

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🏆 Benchmark Highlights — Darwin V7

Our flagship Darwin V7 evolutionary model merging system has produced state-of-the-art results across multiple Korean and English benchmarks:

Model	CLIcK	KMMLU	GPQA	Notes
Darwin-31B-Opus	84.5	76.0	85.9	🥇 Overall #1
Darwin-27B-Opus	82.1	74.3	86.9	🥇 GPQA SOTA
Darwin-14B-Pro	79.8	71.5	82.3	Efficient tier
Lastbrain-MoE	78.2	69.8	80.1	MoE variant

13 models benchmarked across Darwin (8) + Lastbrain (3) + AETHER (2) lineages. See all-leaderboard for full rankings.

What makes Darwin different?

• Evolutionary search over merge recipes — no gradient training required
• Multi-objective optimization — balance Korean fluency, reasoning, and safety
• Transparent lineage tracking — every model is traceable to its parents
• Open weights — releasing under Apache 2.0 where base licenses permit

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🚀 Live Demos on Hugging Face

Flagship Spaces

• 🏆 all-leaderboard — Unified leaderboard across CLIcK, KMMLU, GPQA, HAE-RAE, and more (⭐ 28)
• 💬 QWEN-3_5-CHAT — Qwen 3.5 conversational interface with HF OAuth (⭐ 16)
• 🗣️ fish-s2-pro-zero — Zero-shot speech-to-speech voice cloning (⭐ 3)
• 🤖 openclaw-moltbot — LLM battle arena chatbot (⭐ 6)

Benchmark Suites

• 📊 all-bench — Aggregated benchmark landing
• 📝 EXAM-FINALBENCH — Korean exam-based evaluation

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🗺️ Repository Roadmap

github.com/mayafree-ai/
├── AI                    ← 🌐 Brand landing page (this repo)
├── Huggingface-MAYA      ← 🤗 Mirrored HF Space source code (4 flagship Spaces)
├── darwin-benchmark      ← 📊 (coming) Darwin V7 benchmark results & methodology
├── maya-leaderboard      ← 🏆 (coming) Open leaderboard aggregator
└── maya-chat             ← 💬 (coming) Chat interface deployment templates

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📖 Medium Article Pipeline (shipping weekly)

We publish deep-dive technical articles on Medium covering:

1. "Evolutionary LLM Merging: How Darwin V7 Builds Stronger Models Without Training" (Q2 2026)
2. "Why GPQA 86.9% Matters: Small Models, Big Reasoning" (Q2 2026)
3. "Open Leaderboards for Korean LLMs: A Unified View" (Q2 2026)
4. "From Model Merging to Proto_AGI: The MAYA AI Research Agenda" (Q3 2026)
5. "Building Production Chat Interfaces with HF Spaces OAuth" (Q3 2026)

👉 Follow us on Medium: (link coming soon)

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🧪 Research & Engineering Focus Areas

🧬 Evolutionary Model Merging

Darwin V7 treats LLM weights as a genome. Merge recipes (TIES, DARE, SLERP, ties-dare) act as crossover operators; benchmark suites serve as fitness functions. The system evolves model populations across generations with elitism, mutation, and multi-objective Pareto selection.

🏆 Leaderboard Engineering

We believe leaderboards must be transparent, reproducible, and multi-dimensional. Our all-leaderboard aggregates results across:

• Korean benchmarks: CLIcK, KMMLU, HAE-RAE, KoBEST
• Reasoning benchmarks: GPQA, MMLU, ARC-Challenge
• Chat/Instruction: MT-Bench, AlpacaEval

💬 Conversational Interfaces

Production chat systems require more than a nice prompt. Our chat Spaces ship with HF OAuth, rate limiting, streaming inference, and custom domain routing — a template for deploying LLM services responsibly.

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🛠️ Tech Stack

• Models: Qwen, Llama, Mistral base lineages
• Merging: Custom evolutionary framework (Darwin V7)
• Evaluation: lm-evaluation-harness, custom Korean suites
• Serving: Hugging Face Spaces (Gradio, Docker, Static)
• Infrastructure: AETHER (B200 GPU cluster)

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🤝 Collaborate

We welcome research collaboration, benchmark contributions, and enterprise inquiries.

• 🐦 Twitter: @mayafree_ai
• 🤗 Hugging Face: mayafree | MAYA-AI
• 🌐 Website: mayafree.ai
• 📧 Email: mayafreeai@gmail.com

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📜 License

This landing page repository is licensed under Apache License 2.0.

Individual models and Space sources retain their own licenses as declared in each Space/model card.

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_{Last updated: 2026-04-22 · Maintained by MAYA AI Research}