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Switch all Ollama models to gemma3n:e4b on node-197 GPU

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Bake-off results: gemma3n:e4b (80.6% cmd match, 100% safety, 5.9s)
outperforms qwen3-coder:30b on all metrics. Updated paper, shrink,
and langgraph gateway configs. Frees steel141 for LoRA training.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Claude Code
2026-03-18 10:29:54 -04:00
parent 30aa8388e3
commit ba4a2f4262
4 changed files with 24 additions and 10 deletions
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CONTEXT.md
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@@ -113,3 +113,13 @@ For shrink-world use port `25576` and password `REDACTED_RCON`.
- External access requires port forwarding on router: `25565` and `25566` → `192.168.0.244`
- Web panel accessible via Caddy at `mc.sethpc.xyz`
- DNS: Pi-hole at `192.168.0.153`
---
## AI / Ollama
- **Ollama instance:** `192.168.0.179:11434` (CT 105, node-197, Quadro RTX 4000 8GB)
- **Model (message + command + tool):** `gemma3n:e4b` (6.9B, Q4_K_M, GPU-accelerated)
- **LangGraph gateway model:** `gemma3n:e4b` (was `qwen2.5:1.5b` for tools)
- **Previous:** `192.168.0.141:11434` (steel141), `gemma3:12b` + `qwen3-coder:30b`
- **Changed:** 2026-03-18 after bake-off showed gemma3n:e4b outperforms all tested models