NVIDIA GeForce RTX 3090, 24GB vs AMD Radeon AI PRO R9700, 32GB for local AI
The Radeon AI PRO R9700, 32GB holds 27 of the 39 open models here, and the GeForce RTX 3090, 24GB holds 24. The Radeon AI PRO R9700, 32GB costs $200 less, both priced as the card alone, without the PC around either. On Qwen3.8 27B, the strongest model both hold, the GeForce RTX 3090, 24GB is about 1.3× faster: 38 tok/s against 30, both estimated from memory bandwidth. The Radeon AI PRO R9700, 32GB pays for itself sooner, in 17 years against 19 years at 500k tokens a day. The GeForce RTX 3090, 24GB is the previous generation, so every figure here for it is priced at what it launched at rather than at a price you can pay today.
| NVIDIA GeForce RTX 3090, 24GB | AMD Radeon AI PRO R9700, 32GB | |
|---|---|---|
| Price | $1,499card only | $1,299card only |
| Memory | 24 GB | 32 GB |
| Usable by the GPU | 23 GB | 31 GB |
| Memory bandwidth | 936 GB/s | 640 GB/s |
| Power under load | 350 W | 300 W |
| Models that fit | 24 | 27 |
| Best model it runs | Qwen3.8 27B | Qwen3.8 27B |
| Speed on that model | 38 tok/s estimated | 30 tok/s estimated |
| Pay-back on that model | Pays back in 19 years | Pays back in 17 years |
Run the numbers on the NVIDIA GeForce RTX 3090, 24GB · or the AMD Radeon AI PRO R9700, 32GB
How much use it takes to pay back
Everything above is at 500k tokens a day. Pay-back moves with how much you actually run, so here are both machines on Qwen3.8 27B, the strongest model both hold, at the five levels of use the calculator names. The AMD Radeon AI PRO R9700, 32GB pays back sooner at every level of use, so this is not a choice that turns on how hard you work it.
| A day's use | NVIDIA GeForce RTX 3090, 24GB | AMD Radeon AI PRO R9700, 32GB |
|---|---|---|
| 50ka few chats a day | 191 years | 167 years |
| 200klight assistant use | 48 years | 42 years |
| 1Ma moderate coding-assistant day | 9.6 years | 8.3 years |
| 4Mheavy coding with an agent | 2.4 years | 2.1 years |
| 20Magents running most of the day | 5.7 months | 5.0 months |
Run the NVIDIA GeForce RTX 3090, 24GB at 20M tokens a day · or the AMD Radeon AI PRO R9700, 32GB
What the extra memory buys
The AMD Radeon AI PRO R9700, 32GB holds 3 models the NVIDIA GeForce RTX 3090, 24GB cannot at 32k of context. The strongest of them are what the difference in memory actually buys.
| Model | Weights | Needs at 32k | On the AMD Radeon AI PRO R9700, 32GB |
|---|---|---|---|
| Gemma 4 31B itHaiku-class | 20 GB | 26 GB | 22 tok/s estimated |
| Granite 4.2 30BHaiku-class | 18 GB | 26 GB | 21 tok/s estimated |
| Nemotron 3.5 Lightning 30B-A3BBelow every hosted tier | 25 GB | 26 GB | 127 tok/s estimated |
The assumptions behind both columns
Both columns use the same usage: 500k tokens a day at 15:1 input to output, 32k of context, $0.17 per kWh, and today's API prices held flat. Speeds marked estimated are worked out from memory bandwidth rather than measured, and pay-back scales with them. Graphics cards are priced as the card alone, so add the PC around one before comparing it with a complete computer. Change any of it in the calculator.
More head to head: everything the NVIDIA GeForce RTX 3090, 24GB runs · everything the AMD Radeon AI PRO R9700, 32GB runs · every other match-up · the quickest pay-back at each level of use · every model against the frontier