Qwen3 4B vs 0.6B on a 6 GB GPU: Speed, Memory, and Answer Quality
For my personal retrieval-augmented generation (RAG) study, I needed a local model to answer questions from documents. My laptop has an RTX 3060 Laptop GPU with 6 GiB of VRAM, so memory use mattered alongside speed. I compared qwen3:4b and qwen3:0.6b using Ollama. The smaller model generated tokens roughly three times faster. The larger model passed all six document checks, while the smaller one…
A personal retrieval-augmented generation (RAG) study compared two versions of the Qwen3 model on a laptop with a 6 GB GPU. The smaller 0.6B model generated tokens three times faster than the larger 4B model. However, the 4B model successfully passed all six document checks, while the 0.6B model only passed four. The smaller model had issues combining requirements, missing information, and incorrect output formatting.
The larger model correctly passed all test cases. The findings highlight the trade-off between speed and memory usage, providing a starting point for further exploration.
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