Best GPU for Running LLMs Locally in 2026
By LocalLLMGear Editorial · Editorial Team · Updated 2026-06-28
We test hardware hands-on and may use AI tools in research — every guide is human-reviewed. Editorial policy.
We may earn a commission from links in this article, at no extra cost to you. Disclosure.
Running large language models on your own machine comes down to one number more than any other: VRAM. The model’s weights have to fit in your GPU’s memory, and how much you have decides which models you can run at usable speed. This guide cuts through the spec sheets with picks that actually work — tested, not copied.
The 30-second answer: For most people getting into local LLMs, a used RTX 3090 (24 GB) is still the best value in 2026 — it runs quantized 70B models and every 8B–34B model comfortably. If you want new-with-warranty and more speed, the RTX 4090 / 5090 are the step up.
How much VRAM do you actually need?
A rough rule for quantized (4-bit) models:
VRAM needed to run common model sizes (4-bit quantized)
| GPU / Option | VRAM | Best for |
|---|---|---|
| 7B–8B (Llama 3 8B, Mistral) | 6–8 GB | Entry — runs on most modern GPUs |
| 13B–14B | 10–12 GB | Mid-range cards |
| 32B–34B | 20–24 GB | RTX 3090 / 4090 territory |
| 70B (quantized) | 40–48 GB | Dual-GPU or 48 GB cards |
Our top picks
Best GPUs for local LLMs, 2026
| GPU / Option | VRAM | Price (approx.) | Best for | |
|---|---|---|---|---|
| RTX 3090 (used) ★ Our pick | 24 GB | ~$700–900 | Best value — 70B quantized | Check price → |
| RTX 4090 | 24 GB | ~$1,800 | Fast new card, 24 GB | Check price → |
| RTX 5090 | 32 GB | ~$2,200+ | Top speed + 32 GB headroom | Check price → |
| 2× RTX 3090 | 48 GB | ~$1,600 | 70B at higher quality | Check price → |
Ad · "Check price" links are affiliate links. We may earn a commission at no extra cost to you.
Relative inference speed (Llama 3 8B, 4-bit)
Approximate tokens/sec for a single card running an 8B model — illustrative, based on typical community benchmarks. Use it for relative ordering, not exact numbers.
Why the RTX 3090 is still the value king
Twenty-four gigabytes of VRAM at well under half the price of a new 4090. For local inference — where raw compute matters less than fitting the model — it’s hard to beat. Buy from a reputable seller and check the fans.
When to step up to the 4090 / 5090
If you’re also doing fine-tuning, Stable Diffusion at scale, or you want new-with-warranty, the newer cards are meaningfully faster and the 5090’s 32 GB opens up larger contexts.
Don’t want to buy at all?
If you only need a big GPU occasionally, renting is often cheaper than owning — see our Cloud vs Buy guide. You can spin up an A100 or H100 by the hour:
Rent a GPU on Vast.ai AdFor more on Apple Silicon and multi-GPU setups, see Local LLM Rigs.