VRAMfit guide · updated 2026-06-28

Best GPU for local LLMs (2026)

In short: for local LLMs, buy VRAM first - it decides what you can run - then bandwidth, which sets the speed. A 16 GB card is a great entry point for ~14B models, a 24 GB RTX 4090 runs 30B-class comfortably, and the 32 GB RTX 5090 is the best all-round consumer pick in 2026, with 48-96 GB pro cards for 70B+ work.

Best GPU for local LLMs by tier

Each tier's pick with the biggest model it runs comfortably at Q4_K_M / 8,192 context and VRAMfit's estimated decode speed:

TierPickVRAMBiggest comfortable modelEst. speed
EntryNVIDIA GeForce RTX 5060 Ti 16GB16 GBgpt-oss:20b (20B)~22 tok/s
MidNVIDIA GeForce RTX 508016 GBgpt-oss:20b (20B)~47 tok/s
HighNVIDIA GeForce RTX 409024 GBdeepseek-r1:32b (32B)~31 tok/s
EnthusiastNVIDIA GeForce RTX 509032 GBfalcon:40b (40B)~44 tok/s
ProNVIDIA RTX PRO 6000 Blackwell96 GBzephyr:141b (141B)~12 tok/s

How to choose

Match the tier to the biggest model you want resident in VRAM. There is no compute that rescues a model that does not fit, so the VRAM number is the one that matters; bandwidth then decides whether it feels snappy. Used 24 GB cards (RTX 3090) are the value sweet spot.

The best overall pick

The NVIDIA GeForce RTX 5090 (32 GB) runs 341 catalog models comfortably - up to falcon:40b - and its high bandwidth keeps them fast. Check any card against your shortlist on the fit board.

Frequently asked questions

What is the best GPU for local LLMs in 2026?

For most people the RTX 5090 (32 GB) - it runs the widest range of models comfortably and fast. Drop to a 16 GB card to save money, or a 48-96 GB pro card for 70B+ models.

Is more VRAM or more speed better?

VRAM first: it decides whether a model runs at all. Bandwidth (speed) only matters among cards that already fit the model you want.

Do I need an NVIDIA card?

No - AMD and Intel cards run local LLMs via llama.cpp/Ollama and the VRAM math is identical; NVIDIA is just the most turnkey software path today.

Tool Check your own GPU on the fit board