Best GPU for Llama 3 70B Under $500
Last updated: December 2025
The honest answer: You can't run Llama 3 70B comfortably on a single GPU under $500. But you have options - they just involve tradeoffs.
The VRAM Problem
Llama 3 70B at Q4_K_M quantization needs approximately 40-42GB of VRAM to load the model. At Q8, you're looking at 70GB+. No single consumer or prosumer GPU under $500 offers this.
Your options are:
- Multi-GPU - Split the model across two cards
- Aggressive quantization - Q2/Q3 on a 24GB card (quality loss)
- CPU offloading - Slow, but works with any VRAM
Option 1: Dual Tesla P40 (Best Value)
Cost: ~$300-400 for two cards
Total VRAM: 48GB
Two Tesla P40s give you 48GB of VRAM for under $400. This is enough to run Llama 3 70B at Q4_K_M with room to spare for context.
Pros
- Cheapest path to 48GB VRAM
- Can run 70B at Q4 without quality loss
- Widely available on eBay
Cons
- No display output - headless only
- Needs active cooling (stock is passive/server)
- PCIe 3.0, older Pascal architecture
- Slow generation speed (~8-12 t/s on 70B)
- Multi-GPU adds latency between cards
- Your motherboard needs two x16 slots (or x16 + x8)
What you need
- 2x Tesla P40 24GB (~$150-200 each)
- 2x GPU coolers or 3D printed shrouds with blower fans (~$30-50)
- 750W+ PSU with two 8-pin EPS/CPU connectors (or adapters)
- Motherboard with two PCIe x16/x8 slots
Option 2: Single RTX 3090 + Heavy Quantization
Cost: ~$700-900 used (over budget, but worth mentioning)
VRAM: 24GB
If you can stretch to $700-900, a used RTX 3090 is the better single-card experience. You'll need Q3_K or lower to fit 70B in 24GB, which does impact quality - but you get much faster inference and no multi-GPU headaches.
At 24GB, you can run:
- 70B at Q2_K (~18GB) - noticeable quality loss
- 70B at Q3_K_S (~22GB) - moderate quality loss
- Or run 30B models at Q4-Q6 with excellent quality
Option 3: 24GB Card + CPU Offloading
Cost: $150-400 depending on card
VRAM: 24GB + system RAM
With llama.cpp, you can offload layers to CPU RAM. A Tesla P40 ($150-180) or RTX 3090 ($700-900) can load as many layers as fit in VRAM, with the rest running on CPU.
This works, but expect:
- 2-5 t/s depending on how many layers are offloaded
- You need 64GB+ system RAM
- CPU speed matters (more cores = better)
For occasional 70B use, this is acceptable. For daily use, it's painful.
The Realistic Recommendation
| Setup | Cost | Speed (70B Q4) | Verdict |
|---|---|---|---|
| 2x Tesla P40 | ~$350 | ~8-12 t/s | Best budget option |
| RTX 3090 + Q3 | ~$800 | ~15-20 t/s | Better if you can stretch budget |
| P40 + CPU offload | ~$170 | ~3-5 t/s | Works but slow |
Consider Smaller Models Instead
Honestly? If you're under $500, consider whether you really need 70B.
Llama 3.1 8B runs great on 12GB cards ($150-250) and is surprisingly capable for most tasks.
Qwen 2.5 32B fits comfortably on 24GB at Q4 and outperforms older 70B models on many benchmarks.
Mistral Small (22B) is another strong option that runs well on 24GB.
A single RTX 3060 12GB ($180 used) running an 8B model at 40+ t/s often beats a janky dual-P40 setup running 70B at 10 t/s - especially for interactive use.
Bottom Line
Strict $500 budget? Dual Tesla P40s are your only realistic path to 70B at reasonable quality. Budget $350 for cards, $50-100 for cooling.
Can stretch to $800? A used RTX 3090 with heavy quantization is a better experience.
Want usable daily speeds? Run smaller models. A $200 RTX 3060 12GB running Qwen 2.5 14B will feel faster and more responsive than any budget 70B setup.
Related
- Tesla P100 Review - 16GB HBM2 for fast 7B-14B inference
- Tesla M40 24GB Review - The $80 24GB option
- How we estimate inference speed