Building a Complete Offline AI Development Stack: LM Studio + Ollama + TormentNexus for Air-Gapped Coding

Description and use

Build a fully offline AI development environment with LM Studio, Ollama, and TormentNexus: download models, run a local server, and integrate into your IDE for code completion, chat, and refactoring without cloud exposure.

Problem

Developers in regulated or privacy-sensitive environments need AI-assisted coding without exposing code to cloud services, avoiding latency, cost, and data leakage.

Outcome

The stack delivers responsive, offline AI-assisted coding with first-token latency under 500 ms and 40‑60 tokens/s on a 7B model, eliminating cloud costs and data exposure.

Workflow

• Download and install LM Studio; select and download a suitable code model (e.g., Codestral-7B-EXL2) with appropriate quantization; start the local server to obtain a local API endpoint.
• Install Ollama; pull the same model (e.g., codestral:7b-q4_K_M); run ollama serve to start a persistent local server on port 11434.
• Install TormentNexus CLI and IDE extension; configure it to point to the Ollama endpoint and set the model; enable features such as inline completion, chat, and refactor commands.
• Open a code file in the IDE; use inline completion, context menu refactor, or chat pane to interact with the local LLM; verify that no data leaves the machine.
• Measure performance: expect <500 ms first-token latency and 40‑60 tokens/s generation on a 7B model with an 8 GB GPU.

Evidence

With a well-configured GPU, you can expect first-token latency under 500ms and generation speeds of 40-60 tokens per second on a 7B model—more than sufficient for interactive coding.

Source

TormentNexus is a developer toolkit designed to plug local LLMs directly into your coding workflow.

Source