Points clés
- RTX 3060 12GB ($200–250 used) is the best overall budget pick for 7B–13B models.
- RTX 4060 Ti 8GB ($280–320) offers newer tech and better efficiency but less VRAM.
- Never buy a 2GB or 4GB card for local LLMs—minimum viable VRAM is 8GB for comfortable inference.
- Used enterprise cards (RTX A2000, RTX A4000) offer excellent 12GB–16GB VRAM for $150–250.
- Budget $300–400 for GPU, $400–500 for rest of system (CPU, RAM, SSD) to avoid bottlenecks.
- Avoid DDR5 RAM and high-end CPUs with budget GPUs—they don't improve LLM speed.
What GPU Budget Should You Allocate?
For a functional local LLM rig, plan for $700–1,000 total system cost, with GPU = 30–40% of that budget (~$250–400).
A $250 GPU paired with a $100 CPU creates bottlenecks. A $2,000 GPU with a $30 motherboard wastes money.
As of April 2026, the performance-per-dollar peak is in the $250–350 range (RTX 3060–4070 Super used).
Which Budget GPUs Offer the Best Value in 2026?
- RTX 3060 12GB ($200–250 used): Still the king of budget. Runs Llama 2, Mistral, Qwen 7B smoothly. Older arch, but 12GB VRAM is gold.
- RTX 4060 Ti 8GB ($280–320 new, $200–250 used): Newer, 35% faster per TFLOP than 3060. Drawback: only 8GB. Good for 7B models, tight for 13B.
- RTX 4070 Super ($400–450): Already in "mid-range" territory, but $100–150 more than 4060 Ti. Runs 13B and some 22B models. Overkill if you only want 7B.
- RTX A4000 (Enterprise, used) ($180–230): 16GB VRAM, professional-grade, slightly slower than RTX 3060 per frame but excellent VRAM-to-cost ratio.
How Much VRAM Do You Need for 7B Models?
7B models quantized at Q4 (4-bit) require 6–8GB VRAM; Q5 (5-bit) requires 8–10GB; Q8 (8-bit) requires 14–16GB.
In practice: 8GB is the bare minimum for comfortable inference on 7B models at Q4 with room for batch processing.
6GB cards (RTX 2060) technically work but require aggressive optimization and leave no headroom for higher batches.
Used vs. New: Where Should You Buy?
- Used ($50–100 cheaper): eBay, Facebook Marketplace, Craigslist, local computer repair shops. Higher risk of dead cards or bad VRAM. Always test before committing.
- New ($280–400): Newegg, Amazon, Best Buy, Microcenter. Warranty included. No surprises. Prices stable. Good for risk-averse buyers.
- Mined cards (crypto, dirt cheap): Extreme risk. VRAM degradation common. Only buy if you can fully bench-test on-site.
Common Budget GPU Mistakes
- Buying a 4GB RTX 2060 and expecting smooth 7B inference—you'll hit out-of-memory errors constantly.
- Pairing a $250 GPU with a $30 PSU (power supply)—voltage sag kills stability. Budget 80+ Gold certified, 650W minimum.
- Assuming DDR5 RAM and i9 CPU speed up LLM inference—they don't. GPU VRAM bandwidth is the only bottleneck that matters for inference speed.
FAQ
Is RTX 3060 12GB still worth buying in 2026?
Yes. It's 4+ years old, but 12GB VRAM is timeless. Runs Llama 3 8B and Mistral 7B smoothly. Ideal if you find one used under $250.
Should I buy RTX 4060 or RTX 4060 Ti for local LLMs?
RTX 4060 Ti. The base 4060 (8GB) and 4070 (12GB) are terrible value. The Ti is the best-priced RTX 40-series card for LLM work.
Can I use an AMD RX 6700 or 6800 XT instead?
Yes, but driver support for ONNX Runtime on AMD is weaker than NVIDIA + CUDA. Expect more setup friction. RTX is safer for budgets.
Is 12GB VRAM enough for 13B models?
Barely, at Q4 quantization. Q5 or Q8 will cause OOM errors. If you want 13B comfort, aim for 16GB.
Should I buy a used enterprise GPU like RTX A4000?
Yes, if available. 16GB VRAM, professional-grade cooling, usually $180–230 used. Slightly slower than RTX 3060, but VRAM cushion is worth it.
What PSU wattage should I buy with a $250 GPU?
650W, 80+ Gold minimum. A $250 GPU + CPU + motherboard doesn't exceed 400W draw, but you want headroom for spikes.
Can I run Ollama with a $200 budget GPU?
Yes. Ollama is lightweight. A 4-year-old RTX 3060 with Ollama will run Mistral 7B at 10–15 tokens/sec—totally usable.
Sources
- TechPowerUp GPU Database: RTX 3060 / RTX 4060 Ti / RTX 4070 Super specs and power consumption
- NVIDIA CUDA Capability Matrix: GPU memory bandwidth and theoretical throughput for inference workloads
- Ollama Model Requirements: VRAM recommendations for Llama 2 7B, Mistral 7B, and Qwen quantization levels