Best GPU for Local LLMs
The single biggest factor in which models you can run locally is GPU memory. This guide ranks GPUs by what they unlock — not just raw speed — so you buy the right amount of VRAM for the models you actually need.
VRAM is the gatekeeper
A model only runs if it fits in usable memory. 12GB handles 7–8B models at 4-bit; 24GB opens 32B-class models; 48GB fits a 70B model on one board. Bandwidth then decides how fast tokens generate.
Budget tiers
Entry: RTX 3060 12GB for a first assistant. Value: a used RTX 3090 (24GB). Flagship consumer: RTX 4090 (24GB, fast). Pro single-board 70B: RTX 6000 Ada or A6000 (48GB).
When to go multi-GPU
Two 24GB cards pool to 48GB for capacity and parallelism, but per-card bandwidth still bounds single-model speed. For one large model fast, prefer a single bigger card; for many agents, pool.
Featured chips
Recommended models
- 1Qwen2.5 72BQwen · ~72B · 128K ctx · Qwen License
A top-tier open model for coding and reasoning; a strong backbone for a private Business Command Center.
Minimum: Apple Mac mini (M4 Pro)Recommended: NVIDIA B200 (placeholder) - 2Llama 3.1 70BLlama · ~70B · 128K ctx · Llama Community License
The previous-generation flagship; still excellent. Prefer Llama 3.3 70B where available for similar footprint and better instruction following.
Minimum: NVIDIA RTX A6000Recommended: NVIDIA B200 (placeholder) - 3Llama 3.3 70BLlama · ~70B · 128K ctx · Llama Community License
A flagship open model with near-frontier quality for many business tasks. Full precision needs multi-GPU/datacenter; 4-bit opens it to high-end workstations.
Minimum: NVIDIA RTX A6000Recommended: NVIDIA B200 (placeholder) - 4DeepSeek-R1 Distill Llama 70BDeepSeek · ~70B · 128K ctx · MIT
The largest R1 distill, built on Llama 70B. The strongest locally-runnable reasoning option short of the full MoE; plan for high-end workstation or multi-GPU hardware.
Minimum: NVIDIA RTX A6000Recommended: NVIDIA B200 (placeholder) - 5Mixtral 8x7B (MoE)Mistral · ~47B · 32K ctx · Apache-2.0
Mixture-of-experts: total params are large but only a subset activate per token, so it serves quickly for its quality tier.
Recommended: NVIDIA B200 (placeholder)
Recommended hardware
- 87/100NVIDIA RTX PRO 6000 BlackwellNVIDIA · Professional GPUs
- 66/100NVIDIA GeForce RTX 5090 (placeholder)NVIDIA · Consumer GPUs
- 54/100NVIDIA RTX 6000 Ada GenerationNVIDIA · Professional GPUs
- 52/100AMD Radeon PRO W7900AMD · Professional GPUs
- 50/100NVIDIA RTX A6000NVIDIA · Professional GPUs
- 47/100NVIDIA GeForce RTX 4090NVIDIA · Consumer GPUs
Frequently asked questions
How much VRAM do I need to run a local LLM?+
Budget ~6GB for a 7–8B model at 4-bit, ~20GB for a 32B model, and ~42GB for a 70B model. The 4-bit (Q4) figure is the practical number to plan around.
Is the RTX 4090 the best GPU for local AI?+
It's the best consumer card for speed at 24GB. For 70B models on one board you need a 48GB pro card; for budget, the RTX 3060 12GB or a used 3090 are strong value.