Bigger local LLMs may not always be worth the cost
Choosing a to run locally is hard because and are not easy to compare side by side. Many benchmarks are scattered and do not answer the practical question: which model is actually best to run on your own machine, and which one only makes sense through an API.
Even with enough VRAM to run something around the GLM-5.2 range, it is unclear whether moving to much is worth it. Models in the 70B to 350B range can require far more memory and setup work, while the real-world quality gain may not feel large enough.
Smaller or mid-sized open models, such as Qwen3.6 27B, may be more attractive if they deliver strong quality for their size. The practical issue is the tradeoff between local running cost, hardware burden, setup complexity, and useful output quality.
Key points
- Clear rankings that compare and side by side are hard to find.
- Many benchmarks do not show which models are best for local use versus API use.
- 70B-350B models may add major VRAM needs and setup complexity without a matching quality jump.
- Models like GLM-5.2 and Qwen3.6 27B matter because size efficiency can lower practical costs.
- Agent builders should compare quality, running cost, and maintenance effort, not just model size.