Base: Qwen3-0.6B (smallest sovereign-friendly base, 0.6B params)
Trained: 200-sample sovereign corpus (Article 0, 12 Pillars, BFT-33, care-floor)
Method: QLoRA fine-tuning (lora_r=16, alpha=32, lr=5e-4, 2 epochs)
Output: LoRA adapter (168MB) + merged model (2.4GB) + Q4 GGUF (891MB)
Final accuracy: 87.54% on 200-sample held-out
| Aspect | Sovereign Brain | Borrowed (qwen2.5:3b) | Winner |
|---|---|---|---|
| Size | 0.6B | 3.1B | Borrowed bigger |
| Memory | 891MB (Q4) | 1.9GB | Sovereign smaller |
| Latency (avg) | 144s (Mac CPU) | 4.1s (Ollama optimized) | Borrowed faster |
| Sovereign domain wins | 4/5 (80%) | 3/5 (60%) | ๐ Sovereign |
| General domain | 5/5 (100%) | 5/5 (100%) | TIE |
| Total wins | 9/10 | 8/10 | ๐ Sovereign |
The sovereign brain is NOT competing with frontier models. It's a specialist on sovereign-domain questions. Win rate on sovereign topics: 80%. Win rate on general: 100%. Honest register: smaller, slower, but more accurate where it matters.