Best GPUs for Local LLMs in 2026: VRAM Tiers Explained

Why VRAM Is Everything

For gaming, you look at core count and clock speed. For local AI, there’s one spec that matters above all others: VRAM.

A language model needs to fit entirely in GPU memory to run at full speed. If it doesn’t fit, the model offloads to system RAM — and inference drops from 30+ tokens/second to 2-5 tokens/second. That’s the difference between a responsive assistant and a frustrating wait.

The formula: VRAM needed ≈ (parameters × bits) ÷ 8 + 1GB overhead

Always target Q4 quantization for local use. The quality loss is negligible, and it halves your VRAM requirement compared to Q8.

Tier 1: Budget (6-8GB VRAM) — $150-250

RTX 3060 Ti 8GB ($150-200 used)

• Runs: 3B-7B models at full speed
• Tokens/sec: 30-50 t/s on 7B Q4
• Also handles: Stable Diffusion, basic ComfyUI workflows
• Verdict: Best budget card. We run one of these in our infrastructure — it handles image generation and 7B models without breaking a sweat.

RTX 4060 8GB ($200-250 new)

• Same VRAM as 3060 Ti, slightly faster cores
• Runs: Same models, slightly faster
• Verdict: Buy if you want new with warranty. Used 3060 Ti is better value.

RTX 2060 Super 8GB ($100-150 used)

• Older but still capable for 7B models
• Verdict: Budget emergency pick. Fine for testing, not for daily driver.

Tier 2: Mid-Range (10-12GB VRAM) — $250-400

RTX 3080 10GB ($250-350 used)

• Runs: 7B-9B models at full speed, 13B with slight offload
• Tokens/sec: 40-60 t/s on 7B Q4
• Verdict: Sweet spot for price/performance. We run a 3080 Ti 12GB in our LLM server.

RTX 3080 Ti 12GB ($300-400 used)

• Extra 2GB lets you run 9B models comfortably or 13B with minimal offload
• Verdict: If you find one under $350, grab it.

RTX 4070 12GB ($400-500 new)

• Same VRAM as 3080 Ti, newer architecture, lower power draw
• Verdict: Best new card in this tier. DLSS 3 support if you also game.

Tier 3: Enthusiast (16-24GB VRAM) — $500-900

RTX 3090 24GB ($700-900 used)

• Runs: 13B at full speed, 30B with partial offload
• Tokens/sec: 50-70 t/s on 13B Q4
• Also handles: Large ComfyUI workflows, LoRA training, multiple models simultaneously
• Verdict: The king of used AI GPUs. 24GB opens up 30B models and training. Power hungry (350W).

RTX 4090 24GB ($1500-1800 used)

• Same VRAM, 2x faster cores than 3090
• Verdict: If budget isn’t a concern. Most people don’t need this for local LLMs — the 3090 is 80% as good for half the price.

RTX 4080 Super 16GB ($900-1000 used)

• 16GB — enough for 13B with room for context
• Verdict: Good if you want newer architecture but can’t justify 4090 prices.

Tier 4: Multi-GPU (48GB+ VRAM) — $1400+

2× RTX 3090 (48GB total) ($1400-1800 used)

• Runs: 30B at full speed, 70B with partial offload
• Verdict: The budget AI workstation. Two 3090s in a single rig gives you 48GB for less than a single A100.

RTX A6000 48GB ($2000-3000 used)

• Single card, 48GB — no multi-GPU complexity
• Verdict: Professional workstation card. Overkill for most home users.

What About AMD?

AMD GPUs work with local AI but with caveats:

• ROCm support has improved dramatically in 2026
• Ollama supports AMD GPUs on Linux
• LM Studio added AMD support in 2026
• Performance: 10-20% slower than equivalent NVIDIA cards due to software maturity
• Best AMD picks: RX 7900 XTX 24GB ($700-900), RX 7800 XT 16GB ($450-550)

If you’re starting fresh, NVIDIA is still the path of least resistance. If you already own an AMD card, it’ll work — just expect more setup friction.

What About Apple Silicon?

Apple’s unified memory is a dark horse for local AI:

• M2/M3/M4 Ultra with 128GB+ unified RAM can run 70B models
• No VRAM split — the GPU can access all system memory
• LM Studio and Ollama both support Metal acceleration
• Performance: Slower than a 3090 for 7B models, but can run models that don’t fit on any consumer NVIDIA card

If you already own a high-RAM Mac, you have an AI machine. Don’t overlook it.

Our Recommendation by Budget

Power Supply Matters

Don’t forget power. These cards draw serious wattage:

Next Steps

• Run Your First Local AI Model in 15 Minutes — Get started with any GPU
• Run Local AI with No GPU — CPU-only options
• VRAM Calculator — Check what your card can run

Prices reflect the used market as of September 2026. Check eBay, r/hardwareswap, and Amazon Renewed for current deals.