Ollama, LM Studio, and GPT4All Are All Just llama.cpp — Here's Why Performance Still Differs

Ollama, LM Studio, and GPT4All Are All Just llama.cpp - Here's Why Performance Still Differs When running local LLMs on an RTX 4060 8GB, the first decision isn't the model. It's the framework. llama.cpp, Ollama, LM Studio, vLLM, GPT4All - plenty of options. But under an 8GB VRAM constraint, the framework choice directly affects inference speed. A 0.5GB difference in overhead changes which models you can load at all. One extra API abstraction layer adds a few ms of latency. What follows is a comparison on identical hardware with identical models.