choosing an LLM for a translation project can be confusing.

T5, Flan-T5, Qwen... there are so many open-source options. But how do you know which one is right for your task?

I had a Kinyarwanda–English translation project that wasn't working. I trained a tiny GPT-style model from scratch, and it produced broken sentences like "this is the was to see this" instead of "this door is black."

I needed a real LLM. I started by comparing a few suitable models and looking at four things:

Architecture: Does the model fit my type of task?

Translation needs an encoder-decoder. T5 and Flan-T5 are built for this. Qwen is decoder-only, built for chat and generation.

Hardware: Does it run on a free Google Colab T4 (16 GB)?

Both T5 and Flan-T5 need less than 1 GB. Qwen needs about 9–12 GB. All three fit, but the smaller models train much faster.

Access: Is it free without an API key?

T5, Flan-T5, and Qwen are all Apache 2.0.…