NVIDIA RTX 5090 vs AMD Radeon RX 7900 XTX
Side-by-side local AI comparison: VRAM, memory bandwidth, model compatibility, and estimated tokens per second across 107 open-weight models.
Quick verdict
NVIDIA RTX 5090 wins for local AI inference. It has 8 GB more VRAM and 86.7% more memory bandwidth, runs 58 models natively (vs 57), and exclusively fits 1 model the other cannot. Note: NVIDIA RTX 5090 uses CUDA while AMD Radeon RX 7900 XTX uses ROCM; software ecosystem matters for your framework.
Specs comparison
| Spec | NVIDIA RTX 5090 | AMD Radeon RX 7900 XTX |
|---|---|---|
| VRAM | 32 GB | 24 GB |
| Memory type | GDDR7 | GDDR6 |
| Bandwidth | 1792 GB/s(+87%) | 960 GB/s |
| Architecture | Blackwell | RDNA 3 |
| Backend | CUDA | ROCM |
| Tier | Consumer | Consumer |
| Released | 2025 | 2022 |
| Models (native) | 58 | 57 |
Estimated tokens per second
Computed from memory bandwidth and model active-parameter weight. Assumes model fits natively in VRAM.
| Model | NVIDIA RTX 5090 | AMD Radeon RX 7900 XTX | Delta |
|---|---|---|---|
| Llama 3.3 70B Instruct(70B) | N/A | N/A | N/A |
| Qwen 3.6 27B(27B) | 78.5 t/s(NVFP4) | 36.7 t/s(Q5_K_M) | +66%at Q5_K_M |
| Llama 3.1 8B Instruct(8B) | 78.4 t/s(BF16) | 45.2 t/s(BF16) | +73% |
| Qwen 2.5 7B Instruct(7.6B) | 86.1 t/s(BF16) | 49.4 t/s(BF16) | +74% |
Delta is NVIDIA RTX 5090 relative to AMD Radeon RX 7900 XTX, compared at the highest quantization that fits natively on both cards.
Only NVIDIA RTX 5090 can run(1)
Only AMD Radeon RX 7900 XTX can run(0)
No exclusive models: NVIDIA RTX 5090 can run everything AMD Radeon RX 7900 XTX can.
Both run natively(57)
These models fit in VRAM on both GPUs. Bandwidth determines which runs them faster.
- Mixtral 8x7B Instruct v0.1135.2 t/svs77.8 t/s
- Flint 40B (MoE)196 t/svs94.7 t/s
- Qwen 3.5 35B-A3B (MoE)230.5 t/svs109.8 t/s
- Qwen 3.6 35B-A3B (MoE)230.5 t/svs109.8 t/s
- Ornith 1.5 35B-A3B (MoE)230.5 t/svs109.8 t/s
- Yi 1.5 34B Chat63.4 t/svs39.1 t/s
- Qwen3 32B66.3 t/svs41.5 t/s
- Qwen 2.5 32B Instruct64.5 t/svs40.2 t/s
- Qwen 2.5 Coder 32B Instruct64.5 t/svs40.2 t/s
- DeepSeek R1 Distill Qwen 32B64.5 t/svs40.2 t/s
- Nemotron 3 Nano 30B183.6 t/svs86 t/s
- Gemma 4 31B70 t/svs36.3 t/s
- Qwen3 30B-A3B (MoE)185.3 t/svs85.1 t/s
- Nemotron 3.5 Lightning 30B-A3B176.5 t/svs85 t/s
- Muse Glimmer 30B83 t/svs37.3 t/s
- Gemma 2 27B Instruct75 t/svs38.4 t/s
- +41 more on both
Which should you choose?
- • You need to run larger models (>24 GB VRAM)
- • Faster token generation is the priority
- • You rely on CUDA-based tools (PyTorch, vLLM, Ollama)
- • You want the newer architecture and longer driver support lifecycle
- • Price or availability decides it: AMD Radeon RX 7900 XTX has no VRAM, bandwidth or backend advantage over NVIDIA RTX 5090
Frequently asked questions
- Which is better for local AI, the NVIDIA RTX 5090 or AMD Radeon RX 7900 XTX?
- For local AI inference, the NVIDIA RTX 5090 has the edge. It offers 32 GB VRAM (vs 24 GB) and 1792 GB/s bandwidth (vs 960 GB/s), letting it run 58 models natively in VRAM vs 57 for its rival.
- How much VRAM does the NVIDIA RTX 5090 have vs the AMD Radeon RX 7900 XTX?
- The NVIDIA RTX 5090 has 32 GB of GDDR7 at 1792 GB/s. The AMD Radeon RX 7900 XTX has 24 GB of GDDR6 at 960 GB/s. The NVIDIA RTX 5090 has 8 GB more VRAM, allowing it to run 1 model the AMD Radeon RX 7900 XTX cannot fit natively.
- Can the NVIDIA RTX 5090 run Llama 3.3 70B?
- The NVIDIA RTX 5090 can run Llama 3.3 70B with CPU offload at NVFP4, but at reduced speed.
- Can the AMD Radeon RX 7900 XTX run Llama 3.3 70B?
- The AMD Radeon RX 7900 XTX can run Llama 3.3 70B with CPU offload at Q3_K_M, but at reduced speed.
- What is the difference between the NVIDIA RTX 5090 and AMD Radeon RX 7900 XTX for AI?
- The key difference for AI inference is VRAM and memory bandwidth. The NVIDIA RTX 5090 has 32 GB VRAM at 1792 GB/s (CUDA backend). The AMD Radeon RX 7900 XTX has 24 GB VRAM at 960 GB/s (ROCM backend). VRAM determines which models fit; bandwidth determines tokens per second. The NVIDIA RTX 5090 runs 58 models natively vs 57 for the AMD Radeon RX 7900 XTX.