NVIDIA GeForce RTX 4080 Super vs AMD Radeon RX 7900 XTX
Spec-driven comparison from our catalog. For curated editorial verdicts on the most-asked pairs, see the head-to-head index.
Editorial verdict available: We have a hand-written buyer guide for this exact pair. Read the editorial verdict →
Pick your two cards
Spec matrix
| Dimension | NVIDIA GeForce RTX 4080 Super | AMD Radeon RX 7900 XTX |
|---|---|---|
| VRAM | 16 GB mid (13B-32B Q4; 70B Q4 short ctx) | 24 GB high (70B Q4 comfortable) |
| Memory bandwidth | 736 GB/s acceptable (500-800 GB/s) | 960 GB/s strong (800 GB/s - 1.5 TB/s) |
| FP16 compute | 52.2 TFLOPS | 122.8 TFLOPS |
| FP8 compute | — | — |
| Power draw | 320 W enthusiast (850W PSU) | 355 W enthusiast (850W PSU) |
| Price | ~$1,099 (street) | ~$899 (street) |
| Release year | 2024 | 2022 |
| Vendor | nvidia | amd |
| Runtime support | CUDA, Vulkan | ROCm, Vulkan |
Spec data from our hardware catalog. This is a generated spec compare, not a hand-written editorial verdict. For editorial picks on the most-asked pairs, see our curated head-to-heads.
Most users should buy
AMD Radeon RX 7900 XTX
24 GB usable VRAM unlocks high (70B Q4 comfortable) workloads that the NVIDIA GeForce RTX 4080 Super's 16 GB ceiling can't reach. For most local AI buyers in 2026, VRAM ceiling is the dimension that matters most.
Decision rules
- Your stack is CUDA-locked (vLLM, TensorRT-LLM, FlashAttention, day-zero new model wheels).
- You hate used silicon and want a warranty. The NVIDIA GeForce RTX 4080 Super is the new-with-warranty alternative.
- You target high (70B Q4 comfortable) workloads — 24 GB is the working ceiling for that.
- You're comfortable with used silicon and prioritize $/GB-VRAM.
Biggest buyer mistake on this comparison
Picking the NVIDIA GeForce RTX 4080 Super for the warranty when the AMD Radeon RX 7900 XTX (used) gives you 8 GB more VRAM at lower cost. At the 24 GB tier, used silicon's $/GB-VRAM advantage is decisive — verify ECC error counts before buying, but don't dismiss used out of hand.
Workload fit
How each card handles common local AI workloads. “Tie” means both cards meet the bar; pick on other axes (price, ecosystem, form factor).
| Workload | Winner | Notes |
|---|---|---|
| Coding agents (Aider, Cursor, Continue) | Tie | Code agents work fine on 16 GB for 13-32B models. 24 GB unlocks 70B-class code models (DeepSeek Coder V3, Qwen 2.5 Coder). |
| Ollama / LM Studio chat | Tie | Both run Ollama fine. 16 GB unlocks multi-model serving via OLLAMA_KEEP_ALIVE. |
| Image generation (SDXL, Flux Dev) | AMD Radeon RX 7900 XTX | Image gen is compute-bound. 24 GB VRAM unlocks Flux Dev FP16 + LoRA training. Below 24 GB, Flux Dev FP8 only with offloading. |
| Local RAG (embedding + LLM) | Tie | RAG with 70B LLM concurrent fits at 24 GB. Embedding model overhead is negligible (<1 GB). |
| Long-context chat (32K+ context) | AMD Radeon RX 7900 XTX | 24 GB fits 70B Q4 at 8-16K context. KV cache quantization (Q8 cache) extends to 32K with care. |
| Voice / Whisper transcription | Tie | Whisper Large V3 fits in 4-8 GB. Both cards likely overkill for transcription-only workloads. |
| Video generation (LTX-Video, Mochi) | AMD Radeon RX 7900 XTX | Local video gen viable at 24 GB. Plan for short clips, not long-form. |
VRAM reality check
- Multi-GPU does NOT pool VRAM by default. Two 24 GB cards = 48 GB combined ONLY when the runtime supports tensor-parallel inference (vLLM, ExLlamaV2, llama.cpp split-mode). For models that don't tensor-parallel cleanly, you're stuck at single-card VRAM.
- At 24 GB, 70B Q4 fits with 4-8K context comfortably. FP16 32B fits. 32K+ context on 70B Q4 starts to get tight — KV cache quantization (Q8 cache) extends this another ~30%.
Power, noise, and thermals
- NVIDIA GeForce RTX 4080 Super TDP: 320W. AMD Radeon RX 7900 XTX TDP: 355W. Both fit standard ATX builds with 750-850W PSUs.
- Used cards: replace thermal pads on any used purchase older than 18 months ($30-50 + 1 hour of work). Ex-mining cards specifically — cooler reseat improves thermals 5-10°C, often the difference between throttling and stable load.
Used-market intelligence
- Mining-rig provenance is dominant for used AMD Radeon RX 7900 XTX listings. Not inherently disqualifying — mining wears fans (replaceable) and thermal pads (replaceable), rarely silicon. Verify ECC error counts with nvidia-smi (or vendor equivalent); any value above ~100 = walk away.
- Demand a 30-minute under-load demonstration before paying — screen-recorded inference at 90%+ utilization. Sellers refusing this are red flags.
- Replace thermal pads on any used GPU older than 18 months. Cheap insurance ($30-50 + 1 hour) that often delivers 5-10°C cooler operation under sustained inference.
- Used cards have no warranty. Budget for a 2-3 year operational horizon and plan to resell if your usage tier changes. Used silicon resale is mature in 2026 — selling later is realistic.
Upgrade-path logic
- Don't downgrade VRAM for newer silicon. The NVIDIA GeForce RTX 4080 Super is more recent but ships with 16 GB vs the AMD Radeon RX 7900 XTX's 24 GB. For VRAM-bound local AI workloads, newer-with-less-VRAM is a regression.
- NVIDIA GeForce RTX 4080 Super → AMD Radeon RX 7900 XTX is a real VRAM-tier upgrade (16 GB → 24 GB). Worth it if you're outgrowing the lower-tier ceiling on 70B-class workloads.
Better alternatives to consider
Quick takes
NVIDIA GeForce RTX 4080 Super
Refreshed 4080 with 16GB GDDR6X. Slightly behind 5080 but well-supported.
Full verdict →AMD Radeon RX 7900 XTX
AMD's 24GB challenger to the 4090. ROCm Linux now solid for llama.cpp and vLLM. Best price-per-VRAM-GB on the new market.
Full verdict →