Darwin-4B-Genesis is the 3rd generation Darwin model and the world's first model to successfully crossbreed FFN layers across different architectures — Transformer (Gemma4) and Mamba (Qwen3.5 GatedDeltaNet) — using evolutionary optimization.
The father's Attention layers (Gemma4 Transformer) are preserved at 100%, while the mother's FFN knowledge (Qwen3.5 Mamba) is transplanted at layer-specific optimal ratios discovered automatically by CMA-ES across 42 dimensions.
The result: the child outperforms both parents on every benchmark — a phenomenon known as Hybrid Vigor.
Darwin-4B-Genesis
Why This Matters
1. World First
Existing hybrid models (Jamba, Nemotron-H, Granite 4.0) are all designed and trained from scratch. Darwin-4B-Genesis takes two already-trained models from different architecture families and breeds them evolutionarily — with zero additional training.
2. Hybrid Vigor Demonstrated
Benchmark
David (Father)
Qwen3.5-4B (Mother)
Genesis (Child)
CLIcK
90%
~50% (est.)
92% ✅
MuSR
65%
~55% (est.)
70% ✅
The child surpasses both parents. This is the first demonstration of Hybrid Vigor in AI model breeding.
Benchmarks
Benchmark
Genesis
David (Gen2)
K-AI #1 (27B)
CLIcK (Korean culture)
92%
90%
0.794
MuSR (multi-step reasoning)
70%
65%
0.604
GPQA (deep reasoning)
~60%
~60%
—
How It Works
Cross-Architecture FFN Breeding
Father: Darwin-4B-David (Gemma4 Transformer, hidden=2560, 42 layers)
Mother: Qwen/Qwen3.5-4B (GatedDeltaNet/Mamba, hidden=2560, 32 layers)
Key insight: hidden_size matches (2560) → direct FFN replacement possible
Method: Attention 100% from Father, FFN blended at per-layer optimal ratios
Optimizer: CMA-ES (Covariance Matrix Adaptation Evolution Strategy)
Genome: 42 dimensions (one ratio per layer)
Fitness: CLIcK 60% + MuSR 40% composite score
Frozen layers: L15, L16, L22, L23, L24, L25 (Korean language preservation)
