Gemma 3 QAT Models: Bringing AI to Consumer GPUs

Available on ollama: https://ollama.com/library/gemma3

How many times do I have to say this? Ollama, llamacpp, and many other projects are slower than vLLM/sglang. vLLM is a much superior inference engine and is fully supported by the only LLM frontends that matter (sillytavern).

The community getting obsessed with Ollama has done huge damage to the field, as it's ineffecient compared to vLLM. Many people can get far more tok/s than they think they could if only they knew the right tools.

The significant convenience benefits outweigh the higher TPS that vLLM offers in the context of my single machine homelab GPU server. If I was hosting it for something more critical than just myself and a few friends chatting with it, sure. Being able to just paste a model name into Open WebUI and run it is important to me though.

It is important to know about both to decide between the two for your use case though.

Running any HF model on vllm is as simple as pasting a model name into one command in your terminal.

What command is it? Because that was not at all my experience.