Best AMD vs Best NVIDIA GPU for Local LLMs
AMD vs NVIDIA for local LLMs: RX 7900 XTX (24 GB, ROCm) vs RTX 5090 (32 GB, CUDA) and RTX 4090 (24 GB, CUDA). Software ecosystem, VRAM, bandwidth, and which to choose.
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GPU Comparison
AMD vs NVIDIA for Local LLMs
AMD offers the cheapest new 24 GB card (RX 7900 XTX) with ROCm support. NVIDIA offers the broadest software ecosystem (CUDA), the highest bandwidth, and the only 32 GB consumer option (RTX 5090). Choose based on your software comfort, VRAM needs, and budget.
01 / Specifications
Spec by Spec
02 / Ecosystem
ROCm vs CUDA for Local LLMs
AMD and NVIDIA take fundamentally different approaches to software. ROCm is improving but trails CUDA in breadth of support and Windows compatibility.
AMD (ROCm)
llama.cpp
Full support, all quantizations
Ollama
AMD GPU support
vLLM
ROCm backend
Linux-first
Windows less mature
NVIDIA (CUDA)
Every framework
First-class target for all LLM tools
FP8 + Flash Attention
Out of the box
Windows + Linux
Both platforms seamless
Only 32 GB consumer option
RTX 5090 for unrestricted model access
03 / Strengths & Weaknesses
Pros and Cons
Radeon RX 7900 XTX — Strengths
Strengths
- Cheapest new GPU with 24 GB VRAM
- 960 GB/s bandwidth competitive with RTX 4090
- ROCm support is improving rapidly across major frameworks
- Good value for 70B models at aggressive quantization
Weaknesses
- ROCm ecosystem still lags behind CUDA in tooling and support
- Some quantization formats and optimizations arrive later
- GDDR6 is slightly slower than GDDR6X on bandwidth
GeForce RTX 4090 — Strengths
Strengths
- 1,008 GB/s bandwidth — faster than the new RTX 5080
- 24 GB VRAM opens up 70B-class models
- Full CUDA + FP8 + Flash Attention support
- Significant discount over buying new
Weaknesses
- No warranty on used cards
- 450 W TDP needs a strong PSU and good cooling
- Risk of degraded hardware from mining or heavy use
GeForce RTX 5090 — Strengths
Strengths
- 32 GB VRAM fits most useful models at usable quantizations
- 1,792 GB/s bandwidth — fastest consumer GPU for inference
- Full CUDA ecosystem support with no configuration headaches
- FP8 and Flash Attention 2 support for faster inference
Weaknesses
- 575 W TDP demands a 1,000 W PSU and strong cooling
- Most expensive consumer GPU on the market
- Overkill if you only run 7B-13B models
04 / Verdict
The Bottom Line
AMD Route
Radeon RX 7900 XTX
$750 new, 24 GB, warranty. Best if you run Linux and your frameworks support ROCm. Unbeatable new-card value for 24 GB.
Used NVIDIA
GeForce RTX 4090
~$1,200, 24 GB, CUDA. Best value for 24 GB with full software support. Outperforms every new card in its price range.
Premium NVIDIA
GeForce RTX 5090
$1,999, 32 GB, CUDA. Only option for 70B models at Q4 without offloading. Unrestricted model access.
For more details, see our Best AMD GPU, Best NVIDIA GPU, and main hub pages.
05 / Related
More Comparisons
Frequently Asked Questions
Is AMD ROCm good enough for local LLMs?
Does AMD have a 32 GB consumer GPU?
Is the RX 7900 XTX a good value for LLMs?
Should I switch from NVIDIA to AMD for LLMs?
Looking for specific GPU recommendations? Our main guide covers every budget and VRAM tier.
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