I've been thinking about your budget and I'm so excited for you! I went through this exact struggle a few months back and honestly I love my current setup. I ended up snagging a ZOTAC Gaming GeForce RTX 3060 12GB GDDR6 for way under your $300 limit on the used market and it has been fantastic for my research. Being able to fit the model weights without the system crashing is such a relief! That extra VRAM makes a massive difference when you're trying to meet a tight deadline. Here are a few tips to save cash:

• Look for used listings on eBay or local shops to save $50 or more.
• Triple check it's the 12GB version specifically, not the newer 8GB one.
• Use the saved money for a better power supply if yours is old. You're gonna do great on that paper! Let me know if you need any help with the PyTorch setup...

> Which one actually handles PyTorch better on a budget? Unfortunately, I found out the hard way that raw speed is kinda a trap. I tried a faster card with less memory and it was not as good as expected because my LLMs just kept crashing. For PyTorch, dont get tricked by the 40-series benchmarks, you really need the NVIDIA GeForce RTX 3060 12GB GDDR6 instead. That extra VRAM is the only thing that kept my research project from failing...

Been doing this for years and I learned the hard way that VRAM is king for LLMs. I remember staying up all night for a project because my code kept throwing out of memory errors on a card that was fast but lacked memory. Total nightmare. If you go for a card with only 8GB, you are gonna hit a wall fast. I would suggest sticking with the EVGA GeForce RTX 3060 XC Gaming 12GB GDDR6 because those extra 4GB are the difference between your paper finishing and you staring at a crash report. Just be careful with listings tho, make sure you dont accidentally buy the 8GB variant. Also make sure to check your power supply... people always forget that and then their system reboots mid-training. For a three week deadline, stability beats speed every time.