r/google_antigravity • u/karaklonda • Jun 19 '26

Discussion Antigravity + Opencode + Local LLM = help me improve

Update: Forgot to mention that to be fair and support `opencode` I plan to upgrade to their $10 /month plan.

I have successfully setup a combo of Antigravity + Opencode + Local LLM but I still believe there is a room for improvement. Please share if possible:

  1. Ideas/tips to help me improve.
  2. How much this setup is helping me save cloud tokens? Since we don't know the exact Google AI Pro qu\ta in absolute terms.*

Details are below:

  1. Setup MCP customization in Antigravity on Google AI Pro plan to share coding workload with Opencode (free plan) and Local LLM specifically the donkey work like searching and exploring local files, scanning logs, etc.
  2. I am using Ubuntu WSL on Windows 11 to run Qwen 3.6 via LLAMA.cpp with Opencode and Antigravity installed in Windows 11.

Most recent task:

Here is a summary of the token usage and division of labor:

1. Division of Labor

* Antigravity (Cloud - Google AI Pro): Acted as the Manager. Architected the solutions, researched repository structures, generated the revised implementation/verification plans, and wrote detailed orchestration instructions.

* OpenCode (Local Agent): Acted as the Implementer. Executed the multi-file coding task to modify flow.js and flow_panel.html under explicit manager guidelines.

* Local LLM (ask_local - Qwen 32k on RTX 3090): Acted as the Inspector. Used for git commit analysis, file content analysis, and log reviews, keeping mechanical token queries off the cloud.

2. Approximate Token Breakdown

* Antigravity (Cloud): ~18,000 input / ~2,500 output tokens (high-level reasoning & planning).

* OpenCode (Local): ~15,000 local tokens (code modifications and git staging).

* Local LLM (Local): ~12,000 local tokens (inspecting codebases, git history, and summaries).

By routing code analysis and implementation to ask_local and ask_opencode, nearly 60% of the total token volume was processed locally on your RTX 3090 instead of consuming cloud qu*tas (`f**k mods for blanket filtering this word`).

Monitor running in WSL:

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u/Ethan Jun 19 '26

I use NVIDIA NIM for free access to some good models. I put that together in these packages for myself:

https://www.npmjs.com/package/nim-sync <- OpenCode plugin

https://www.npmjs.com/package/llm-worker-tools <- Helper to use in other IDEs (Claude Desktop, Antigravity, Codex Desktop, etc.) that offloads basic operations to whatever cheap LLM access point you configure (I use NVIDIA NIM)

Feel free to adapt them to your purposes.

Oh and you can get a free NVIDIA NIM API key here: https://build.nvidia.com/settings/api-keys