Most companies assume private ChatGPT accounts or enterprise agreements guarantee zero telemetry. In practice, prompt caching endpoints, DNS lookups, and unmonitored API sockets routinely expose internal codebases and spreadsheets to WAN traffic.
Over the past few weeks, we benchmarked an air-gapped local stack using Ollama + Llama 3 70B (and DeepSeek R1). By restricting socket binding strictly to 127.0.0.1, offloading 48 GPU layers, and disabling external telemetry in the YAML daemon, we got consistent 50 tokens/second throughput on a single local workstation with $0 cloud API cost.
Key configuration takeaways:
- Restrict listening host to
127.0.0.1:11434(drop 0.0.0.0 to prevent LAN leaks). - Force flash-attention and tune context windows to 8192 for FP8/Q4 models.
- Disallow remote CORS origins entirely.
If anyone is building an offline AI setup for compliance/finance and wants the exact ghost-mode-config.yaml file, terminal quick-launch script, and the breakdown video, I put it up open-source here:
https://pulsehubpro.com/ghost-mode/
How is your team handling local vs cloud inference compliance right now?
Source: r/GoogleColab · by /u/Minimum_Plate_3900