TL;DR: Under $300, your options are limited but workable. Expect 7B–8B models and you'll be fine. Expect 13B+ and you'll be frustrated. The Arc B580 is the clear winner at this tier — nothing else at $300 or below gives you 12GB VRAM at competitive bandwidth.
Bottom line: Arc B580 ($250) is the pick. Buy it if you want the best under-$300 AI GPU today.
The Reality of the Sub-$300 Tier
At under $300, you're in 7B–8B model territory. That means:
Good for: Chat assistants, email drafting, summarization, simple coding (Python scripts, debugging), document Q&A, offline research
Not good for: Complex reasoning, nuanced writing, large codebase analysis, anything requiring instruction-following at a high level
A well-quantized Llama 3.1 8B at Q4_K_M is genuinely useful for these tasks. Manage expectations and you'll be happy. Expect GPT-4 and you won't.
Software support is also a bigger factor at this tier. Cheaper GPUs often have worse driver support, limited compatibility with newer frameworks, or quirky behavior with certain model formats.
The 5 GPUs
1. Intel Arc B580 — ~$250
12GB GDDR6, 456 GB/s. The best overall pick under $300. More VRAM than anything else at this price. Works with Ollama and llama.cpp (the two most popular local AI tools). Runs Llama 3.1 8B at ~35–38 tok/s.
Caveat: ROCm compatibility issues for non-standard setups. Stick to GGUF models via Ollama and you'll be fine. Venture into ComfyUI or experimental frameworks and you may hit walls.
Want to see how the B580 stacks up against 16GB options? See the 16GB GPU comparison. If you can stretch your budget slightly, the RTX 5060 Ti 16GB is worth watching — though pricing is already creeping above MSRP.
2. RTX 3060 12GB — ~$270 used
12GB GDDR6, 360 GB/s. NVIDIA ecosystem, so zero compatibility issues. Slower bandwidth than the B580, which shows up in inference speed (~30 t/s on 8B Q4).
Why consider it over the B580: if you want NVIDIA reliability and don't want to deal with Arc driver quirks. Worth paying the slight premium for peace of mind.
3. RTX 3060 Ti 8GB — ~$200 used
8GB GDDR6, 448 GB/s. Only 8GB VRAM — this is a hard constraint. You're locked to 7B models at Q4. Can't run 13B at any useful quality.
Why it's on this list: it's cheap, fast for 7B, and completely reliable software-wise. If 8GB is genuinely enough for your use case, it's a solid choice. Most people will want more VRAM though.
4. RX 6700 XT 12GB — ~$250 used
12GB GDDR6, 384 GB/s. AMD card with ROCm support. Better supported than Arc in the AMD ecosystem, but ROCm on Windows is still rougher than CUDA on NVIDIA. Linux users will have a better experience.
Honest take: unless you're on Linux and comfortable with ROCm, the Arc B580 beats this at the same price. NVIDIA compatibility advantage aside, Arc has better Windows software support right now.
5. RTX 2080 Ti 11GB — ~$200 used
11GB GDDR6, 616 GB/s. High bandwidth for an older card. Runs 7B models fast (~45 t/s on 8B Q4) because of the bandwidth. But 11GB VRAM is an awkward number — you're just short of comfortable 13B territory.
Worth it if you find one under $200 and want fast 7B inference. Avoid at $250+.
The Ranking
- Arc B580 — best overall, 12GB, best price
- RTX 3060 12GB — best for reliability, slightly slower
- RX 6700 XT — good on Linux, okay on Windows
- RTX 2080 Ti — fast if cheap, awkward VRAM
- RTX 3060 Ti 8GB — fine for strict 7B use, limited ceiling
Ready to go beyond $300? See what the cheapest path to running Llama 3 looks like across all tiers.
Unsure if 8–12GB will be enough for what you want to run? Check the VRAM requirements by model size.
For the full picture across all price ranges, see our complete GPU comparison guide.