Short answer: choose the Radeon RX 7900 XTX when your exact workload benefits from 24GB and your tested ROCm stack supports it. Choose the GeForce RTX 5080 when 16GB is enough and CUDA compatibility or a current Blackwell path matters more than the extra 8GB. The RX 7900 XTX has the larger memory pool; the RTX 5080 is not automatically faster for every local-AI workload just because it is newer.
RX 7900 XTX versus RTX 5080 specifications
| Planning input | RX 7900 XTX reference | RTX 5080 Founders Edition |
|---|---|---|
| Architecture | AMD RDNA 3 | NVIDIA Blackwell |
| Memory | 24GB GDDR6 | 16GB GDDR7 |
| Memory interface | 384-bit | 256-bit |
| Published processing units | 6,144 stream processors / 96 compute units | 10,752 CUDA cores |
| Published bandwidth | Up to 960GB/s | 960GB/s |
| Boost clock | Up to 2.5GHz | 2.62GHz |
| Board power | 355W typical board power | 360W total graphics power |
| Recommended system power | 800W | 850W |
| Reference power input | 2 × 8-pin | 1 × 450W+ Gen 5 cable or supplied 3 × 8-pin adapter |
| Reference dimensions | 287mm, 2.5-slot | 304mm × 137mm, 2-slot card; NVIDIA advises adjacent airflow clearance |
| Primary software path | ROCm; verify the exact OS, framework and operator set | CUDA; verify current Blackwell / compute capability 12.0 support |
Start with the dedicated RX 7900 XTX 24GB guide or RTX 5080 16GB guide. Compare the broader 24GB GPU paths and 16GB GPU paths before treating either card as the default.
What 16GB versus 24GB changes for a 32B model
These are official Qwen2.5-32B-Instruct GGUF file sizes. Raw margin means advertised device memory minus file size; it excludes KV cache, runtime workspace, allocator overhead and display use. A positive number is not a guarantee that the complete run fits.
| Official artifact | File size | 16GB raw margin | 24GB raw margin |
|---|---|---|---|
| Q2_K | 12.3GB | 3.7GB | 11.7GB |
| Q3_K_M | 15.9GB | 0.1GB — unsafe planning margin | 8.1GB |
| Q4_K_M | 19.9GB | Does not fit by file size | 4.1GB |
| Q5_K_M | 23.3GB | Does not fit | 0.7GB — unsafe planning margin |
| Q6_K | 26.9GB | Does not fit | Does not fit; 2.9GB over |
The official Q4_K_M file is already 3.9GB larger than a 16GB card before overhead, while it leaves 4.1GB of raw margin on 24GB. That is a capacity difference, not a tokens-per-second result. Review the 32B VRAM requirements and stage a matched benchmark rather than comparing an offloaded 16GB run with a resident 24GB run.
The software fork: ROCm or CUDA
ROCm support is version-, operating-system-, framework- and operator-specific. CUDA has broader application coverage, but Blackwell support also depends on current drivers and builds. Verify the exact backend, unsupported operators and fallback behavior for the application you will actually use. The CUDA versus ROCm guide provides a pre-purchase checklist.
How to choose without a misleading benchmark
- Choose the exact model artifact, context, cache type and concurrency first.
- If measured peak use comfortably fits within 16GB and the required software works on Blackwell, compare the RTX 5080 on price, speed and power using the same workload.
- If the artifact or representative peak crosses 16GB but fits within 24GB, the RX 7900 XTX avoids part or all of the offload—provided the ROCm path is functional.
- Record exact board, OS, driver, backend/runtime, fallback, CPU offload, exposed memory, peak use, power limit and wall power.
- Do not combine two cards into one assumed memory pool. Multi-GPU model partitioning must be explicit.
After the fit and software checks, review screened hardware offers. Current seller price and condition—not launch MSRP—belong in the final value comparison.