README.md

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title: GOBA-AI-Labs
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# GOBA-AI-Labs

**Making large AI models accessible on consumer hardware.**

We develop open-source tools for compressing Mixture-of-Experts (MoE) AI models. Our expert pruning technology reduces model sizes by 50-90% while preserving quality — enabling 400B+ parameter models to run on laptops with 24GB RAM.

## PrunedHub Models

Calibration-based expert pruning with zero retraining. Drop-in replacements for llama.cpp.

| Model | Base | Size | Quality | Highlights |
|-------|------|------|---------|------------|
| [PrunedHub GPT-OSS-20B-28x](https://huggingface.co/GOBA-AI-Labs/PrunedHub-GPT-OSS-20B-28x) | GPT-OSS-20B | 10.4 GB | MMLU 78% (lossless) | Zero quality loss, fits 16GB RAM |
| [PrunedHub GPT-OSS-20B-27x-Zerobias](https://huggingface.co/GOBA-AI-Labs/PrunedHub-GPT-OSS-20B-27x-Zerobias) | GPT-OSS-20B | ~9.4 GB | MMLU 77% (-1pp) | Experimental router optimization |
| [PrunedHub Qwen3-30B-A3B-JP-80pct](https://huggingface.co/GOBA-AI-Labs/PrunedHub-Qwen3-30B-A3B-JP-80pct) | Qwen3-30B-A3B | 14.0 GB | MMLU 79% (think-ON) | Language-aware pruning, Japanese quality preserved |
| [PrunedHub Qwen3-Coder-Next-50pct](https://huggingface.co/GOBA-AI-Labs/PrunedHub-Qwen3-Coder-Next-50pct) | Qwen3-Coder-Next | 24.4 GB | MMLU 72% | 80B model in 24GB, outperforms Q2 quantization |

## Our Approach

Traditional model compression relies on aggressive quantization, which degrades all computations uniformly. Our expert pruning takes a fundamentally different approach — removing entire redundant computation paths from MoE models while keeping the remaining experts at full precision.

- **Calibration-based importance scoring** — Expert importance measured through actual inference behavior, not static weight analysis
- **Layer-adaptive expert allocation** — Each layer retains a dynamically determined number of experts based on its contribution to quality
- **Language-aware optimization** — Automatic detection and protection of language-specialized experts
- **Zerobias router optimization** — Post-pruning router bias correction that extends the lossless compression frontier

## Links

- [Support us on Ko-fi](https://ko-fi.com/gobaailabs)