Best GPU for Local AI in 2026
Updated September 20, 2026. Specs and launch MSRP from the CompareAIHardware products database (price_checked_at 2026-09-02). Street / current_new is NULL on every ranked row. Token speeds only where a non-quarantined benchmark row exists.
Verdict. Best overall local-AI GPU: NVIDIA GeForce RTX 5090 — 32 GB GDDR7, 1,792 GB/s, 575 W, launch MSRP $1,999. Measured 215 tok/s on Llama-3.1-8B Q4_K_M (llama.cpp b3500 CUDA). Best value 24 GB: used GeForce RTX 3090 (launch MSRP $1,499; no current_new). Best new budget: Intel Arc B580 — 12 GB, $249 launch MSRP, 41 tok/s on the same 8B Q4_K_M row (Vulkan). Best workstation: RTX PRO 6000 Blackwell — 96 GB GDDR7 ECC, 1,792 GB/s, 600 W; launch MSRP NULL.
This hub answers the head phrase best GPU for local AI. It is not a copy of Best GPU for Local LLMs (shortlist) or Best GPUs for LLM Inference (full inference pillar). Rank uses VRAM first, then memory bandwidth, then T06 price class. T06 classes on this page: launch_msrp from products.msrp_usd; current_new and used-median are not on file (street_price_usd is NULL).
On this page
Which GPU wins each local-AI tier?
Arc B580 (product id 9) stores 12 GB GDDR6 at 456 GB/s and 190 W. It is the cheapest available consumer GPU in the database that still has a sourced Llama-3.1-8B Q4_K_M generation row: 41 tok/s on llama.cpp Vulkan (runaihome.com). NVIDIA alternative: GeForce RTX 3060 12GB (id 32) — 12 GB GDDR6, 360 GB/s, 170 W, launch MSRP $329, 38 tok/s on the same model/quant (llama.cpp b3500 CUDA).
RTX 5070 Ti (id 17) is 16 GB GDDR7, 896 GB/s, 300 W, launch MSRP $749. Sourced generation: 87.54 tok/s on Qwen3-8B Q4_K_XL (llama.cpp llama-bench, CUDA 12.8). No Llama-3.1-8B Q4_K_M row — that cell stays n/a. Faster 16 GB card with an 8B row: RTX 5080 (id 2) — 16 GB GDDR7, 960 GB/s, 360 W, $999 launch MSRP, 132 tok/s Llama-3.1-8B Q4_K_M. Cheaper 16 GB: RTX 5060 Ti 16GB (id 19) $429 / 448 GB/s / 51.41 tok/s Qwen3-8B Q4_K_XL; RTX 4060 Ti 16GB (id 5) $499 / 288 GB/s / 34.31 tok/s Qwen3-8B Q4_K_XL.
RTX 3090 (id 6, status eol) is 24 GB GDDR6X, 936 GB/s, 350 W, launch MSRP $1,499. Sourced 85 tok/s Llama-3.1-8B Q4_K_M. New 24 GB: RTX 4090 (id 3) — 24 GB GDDR6X, 1,008 GB/s, 450 W, $1,599 launch MSRP, 125 tok/s same 8B row. AMD 24 GB: RX 7900 XTX (id 7) — 24 GB GDDR6, 960 GB/s, 355 W, $999 launch MSRP, 76 tok/s on ROCm. Used-median T06 class is not stored; treat the 3090 as launch_msrp plus used-market risk, not a live used price.
RTX 5090 (id 1) is the only available consumer GPU in the database with 32 GB. Specs: GDDR7, 1,792 GB/s, 575 W, launch MSRP $1,999. Sourced 215 tok/s Llama-3.1-8B Q4_K_M (not an estimate). Llama-3-70B Q4 generation is 42 tok/s and is_estimate=1 (Tom's Hardware). SDXL Turbo is 120 img/min (not an estimate).
RTX PRO 6000 Blackwell (id 63): 96 GB GDDR7 ECC, 1,792 GB/s, 600 W. msrp_usd is NULL — do not invent a workstation street or list price. Sourced 140.62 tok/s on Qwen3-8B Q4_K_XL. Priced alternative with a number: RTX 6000 Ada (id 12) — 48 GB GDDR6, 960 GB/s, 300 W, launch MSRP $6,800, 110 tok/s Llama-3.1-8B Q4_K_M; Llama-3-70B Q4 35 tok/s is an estimate.
How do the ranked cards compare on the database?
Every cell is a products / specifications / benchmarks row. Missing benches print n/a. Estimates carry an asterisk.
| GPU | VRAM | Type | BW | TDP | launch_msrp | current_new | Llama-3.1-8B Q4_K_M tok/s | Qwen3-8B Q4_K_XL tok/s |
|---|---|---|---|---|---|---|---|---|
| GeForce RTX 5090 | 32 GB | GDDR7 | 1,792 GB/s | 575 W | $1,999 | NULL | 215 | 145.34 |
| GeForce RTX 5080 | 16 GB | GDDR7 | 960 GB/s | 360 W | $999 | NULL | 132 | 94.14 |
| GeForce RTX 4090 | 24 GB | GDDR6X | 1,008 GB/s | 450 W | $1,599 | NULL | 125 | 104.31 |
| RTX 6000 Ada | 48 GB | GDDR6 | 960 GB/s | 300 W | $6,800 | NULL | 110 | 98.68 |
| GeForce RTX 4080 SUPER | 16 GB | GDDR6X | 736 GB/s | 320 W | $999 | NULL | 102 | 79.36 |
| RTX PRO 6000 Blackwell | 96 GB | GDDR7 ECC | 1,792 GB/s | 600 W | NULL | NULL | n/a | 140.62 |
| GeForce RTX 5070 Ti | 16 GB | GDDR7 | 896 GB/s | 300 W | $749 | NULL | n/a | 87.54 |
| GeForce RTX 3090 (eol) | 24 GB | GDDR6X | 936 GB/s | 350 W | $1,499 | NULL | 85 | 87.45 |
| Radeon RX 7900 XTX | 24 GB | GDDR6 | 960 GB/s | 355 W | $999 | NULL | 76 | n/a |
| GeForce RTX 5060 Ti 16GB | 16 GB | GDDR7 | 448 GB/s | 180 W | $429 | NULL | n/a | 51.41 |
| Arc B580 | 12 GB | GDDR6 | 456 GB/s | 190 W | $249 | NULL | 41 | n/a |
| GeForce RTX 3060 12GB | 12 GB | GDDR6 | 360 GB/s | 170 W | $329 | NULL | 38 | 41.97 |
| GeForce RTX 4060 Ti 16GB | 16 GB | GDDR6 | 288 GB/s | 160 W | $499 | NULL | n/a | 34.31 |
Llama-3-70B Q4 tok/s (estimates, is_estimate=1): RTX 5090 42 · RTX 6000 Ada 35 · RTX 4090 18. Not shown as measured.
What does T06 price class mean here?
T06 names three price bases: launch_msrp (products.msrp_usd), current_new (dated street / street_price_usd), and used-median. On 2026-09-20 every GPU in this ranking has street_price_usd NULL, so every printed dollar is launch MSRP. RTX PRO 6000 Blackwell has msrp_usd NULL — printed as NULL, not guessed. Affiliate CTAs say “Check current price” because Amazon is not a current_new feed.
How did we rank these GPUs?
VRAM capacity first (what local models fit). Memory bandwidth second (generation speed once the model fits). T06 launch_msrp third. Token speeds only from benchmarks.quarantined=0. Estimates labeled. Unknowns stay n/a or NULL. Affiliate links do not change rank. Full process: methodology.
Frequently Asked Questions
What is the best GPU for local AI in 2026?
The GeForce RTX 5090 is the best overall consumer pick in our database: 32 GB GDDR7, 1,792 GB/s, and a measured 215 tok/s on Llama-3.1-8B Q4_K_M. Buy a used RTX 3090 if 24 GB at launch-MSRP $1,499 is the budget, or an Arc B580 if the budget is $249 launch MSRP and 12 GB is enough.
Is this the same page as Best GPU for LLMs?
No. /best-gpu-for-llms is the shortlist pillar. /best-gpus-for-llm-inference is the inference-depth pillar. This URL targets the head phrase “best GPU for local AI” and is meant to refresh monthly from the same live tables.
Why are some prices NULL?
We do not invent street or workstation list prices. current_new is NULL across this set. RTX PRO 6000 Blackwell also has NULL launch MSRP.
Can AMD or Intel run local AI?
Yes. RX 7900 XTX has a sourced 76 tok/s Llama-3.1-8B Q4_K_M row on ROCm. Arc B580 has 41 tok/s on Vulkan. CUDA cards still have the widest tool coverage.
Sources
- NVIDIA GeForce RTX 5090 datasheet — https://www.nvidia.com/en-us/geforce/graphics-cards/50-series/rtx-5090/
- NVIDIA GeForce RTX 5080 datasheet — https://www.nvidia.com/en-us/geforce/graphics-cards/50-series/rtx-5080/
- NVIDIA GeForce 40-series — https://www.nvidia.com/en-us/geforce/graphics-cards/40-series/
- NVIDIA GeForce 30-series — https://www.nvidia.com/en-us/geforce/graphics-cards/30-series/
- NVIDIA RTX 5070 family — https://www.nvidia.com/en-us/geforce/graphics-cards/50-series/rtx-5070-family/
- NVIDIA RTX PRO 6000 Blackwell — https://www.nvidia.com/en-us/products/workstations/professional-desktop-gpus/rtx-pro-6000/
- NVIDIA RTX 6000 Ada — https://www.nvidia.com/en-us/design-visualization/rtx/6000-ada-generation/
- AMD Radeon 7000 series — https://www.amd.com/en/products/graphics/desktops/radeon/7000-series.html
- llama.cpp / llama-bench community benches — https://www.myaihardware.com/llama-cpp-benchmarks/
- hardware-corner GPU ranking (Qwen3-8B) — https://www.hardware-corner.net/gpu-ranking-local-llm/
- localaimaster RTX 5090 vs 5080 — https://localaimaster.com/blog/rtx-5090-vs-5080-local-ai
- Arc B580 local AI 2026 — https://runaihome.com/blog/intel-arc-b580-local-ai-2026/
- Tom's Hardware GPU benches — https://www.tomshardware.com/pc-components/gpus
- CompareAIHardware methodology — https://compareaihardware.com/methodology
Related: Best GPU for Local LLMs · Best GPUs for LLM Inference · VRAM calculator · Model fit index · GPU comparisons.
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