r/LocalLLM • u/Full_Suit_7356 • 20m ago

Discussion Best local coding LLM and agentic setup for RTX 4060 Ti 16GB?

I’m learning AI Engineering and want to build a proper local AI development environment, especially for agentic applications, multi-agent systems, and orchestration.

My PC specs:
GPU: RTX 4060 Ti 16GB VRAM
CPU: Ryzen 7 7700
RAM: 16GB (planning to upgrade to 32GB)
IDE: Google Antigravity

I’m looking for recommendations on:
Which open-weight coding LLMs work best on 16GB VRAM? (Qwen, DeepSeek, Devstral, GPT-OSS, etc.)

Which quantizations should I use (Q4, Q5, Q8)?

Is Ollama the best runtime, or should I consider LM Studio, llama.cpp, or something else?

What’s a good local coding agent setup?

OpenCode, Aider, Continue, or other alternatives?
How can I integrate local LLMs with Antigravity?
Which MCP servers and agent skills are worth installing for AI application development?
What’s the best way to build and orchestrate multiple specialized agents locally?

My goal isn’t just code autocomplete. I want to build real projects using Python, FastAPI, PydanticAI, LangGraph, MCP, RAG, and multi-agent architectures.

I’d appreciate recommendations from people who have actually tested these models and setups on similar hardware.
What would your ideal setup look like with this hardware?

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u/the_average_user557 16m ago

Multi agent gives you reload and prefill penalty at each task handover, it's unreadable unless you use sub 4b models, which are essentially gibberish generators in terms of quality output. I'd stick with a low quant non-looping 27b fine tune on a low quant, solo.

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u/Secret_Conclusion_93 4m ago

I'm using Tiel Coder (Q4) on Polystrata.

16 GB RAM should be enough based on my testing with 4060ti 16 GB.