NVIDIA GeForce RTX 5090
32 GB · 1,792 GB/s · 575 W
Prices
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What it runs
Every model in the catalogue, with the best quant for this hardware. Estimates, not measurements.
| Model | Quant | Fits | Memory | Max context | Decode @64k | Prefill | Good for |
|---|---|---|---|---|---|---|---|
| Qwen 3.8 27B Alibaba Qwen | UD-Q6_K | fits | 25.7 GB | 147k256k with q8 cache | 42tok/sest. | 1374 tok/s | chat, coding, agents, long documents |
| Qwen 3.6 27B Alibaba Qwen | Q6_K | fits | 26.2 GB | 140k245k with q8 cache | 41tok/sest. | 1374 tok/s | chat, coding, agents, long documents |
| Gemma 4 31B | Q6_K | fits | 30.3 GB | 76k143k with q8 cache | 35tok/sest. | 1255 tok/s | chat, coding, agents |
| Qwen 3.6 35B-A3B Alibaba Qwen | UD-Q6_K | fits | 29.7 GB | 131k206k with q8 cache | 173tok/sest. | 8273 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 27B Alibaba Qwen | Q6_K | fits | 26.1 GB | 141k246k with q8 cache | 41tok/sest. | 1374 tok/s | chat, coding, agents, long documents |
| Gemma 4 26B-A4B | Q8_0 | fits | 27.5 GB | 216k256k with q8 cache | 117tok/sest. | 8470 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q6_K | fits | 29.3 GB | 148k232k with q8 cache | 175tok/sest. | 8273 tok/s | chat, coding, agents, long documents |
| GLM 4.7 Flash Z.ai | Q6_K | fits | 27.4 GB | 133k198k with q8 cache | 87tok/sest. | 4104 tok/s | chat, coding, agents, long documents |
| Devstral Small 2 24B Mistral AI | Q6_K | fits | 29.1 GB | 78k142k with q8 cache | 37tok/sest. | 1353 tok/s | chat, coding, agents |
| Kimi Linear 48B-A3B Moonshot AI | Q4_K_M | fits | 29.6 GB | 196k267k with q8 cache | 277tok/sest. | 6645 tok/s | chat, coding, long documents |
| gpt-oss 20B OpenAI | MXFP4 | fits | 13.9 GB | 128k | 165tok/sest. | 6332 tok/s | chat, coding, agents, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q6_K | fits | 30.4 GB | 73k131k with q8 cache | 75tok/sest. | 2960 tok/s | chat, coding, agents |
| Gemma 4 12B | Q8_0 | fits | 14.2 GB | 256k | 79tok/sest. | 3256 tok/s | chat, coding, long documents |
| Qwen 3.5 9B Alibaba Qwen | Q8_0 | fits | 12.0 GB | 256k | 95tok/sest. | 3985 tok/s | chat, coding, long documents |
| Gemma 3 27B | Q6_K | fits | 27.1 GB | 114k128k with q8 cache | 40tok/sest. | 1539 tok/s | chat, coding, long documents |
| Mistral Small 3.2 24B Mistral AI | Q6_K | fits | 29.1 GB | 78k128k with q8 cache | 37tok/sest. | 1353 tok/s | chat, coding |
| Ministral 3 14B Mistral AI | Q8_0 | fits | 24.4 GB | 106k194k with q8 cache | 44tok/sest. | 1905 tok/s | chat, coding |
| Qwen3 14B Alibaba Qwen | Q8_0 | fits | 25.7 GB | 40k | 42tok/sest. | 1668 tok/s | chat, coding |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q8_0 | fits | 18.2 GB | 128k | 61tok/sest. | 2634 tok/s | chat, coding, long documents |
| Qwen3 8B Alibaba Qwen | Q8_0 | fits | 18.2 GB | 40k | 61tok/sest. | 2634 tok/s | chat, coding, long documents |
| Phi-4 14B Microsoft | Q8_0 | fits | 28.1 GB | 16k | 38tok/sest. | 1675 tok/s | chat, coding |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 7.3 GB | 256k | 166tok/sest. | 6908 tok/s | chat, coding, long documents |
| Ministral 3 8B Mistral AI | Q8_0 | fits | 18.0 GB | 160k256k with q8 cache | 61tok/sest. | 2606 tok/s | chat, coding, long documents |
| Granite 4.2 8B IBM | Q8_0 | fits | 19.8 GB | 128k | 55tok/sest. | 2408 tok/s | chat, coding, agents, long documents |
| Gemma 4 E4B | Q8_0 | fits | 10.5 GB | 128k | 110tok/sest. | 5220 tok/s | chat, coding, long documents |
| LFM2.5 8B-A1B Liquid AI | Q8_0 | fits | 12.5 GB | 125k | 156tok/sest. | 11140 tok/s | chat, coding, long documents |
| Llama 3.1 8B Meta | Q6_K | fits | 15.2 GB | 128k | 73tok/sest. | 2829 tok/s | chat, coding, long documents |
| Qwen 3.5 122B-A10B Alibaba Qwen | UD-Q2_K_XL | offload | 41.7 GB | – | 22tok/sest. | 2425 tok/s | chat, coding |
| Qwen3 Coder Next Alibaba Qwen | Q4_K_M | offload | 47.8 GB | – | 21tok/sest. | 5229 tok/s | chat, coding |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q2_K_XL | offload | 52.6 GB | – | 12tok/sest. | 2503 tok/s | – |
| Mistral Small 4 119B Mistral AI | UD-Q2_K_XL | offload | 39.9 GB | – | 32tok/sest. | 2442 tok/s | chat, coding, agents, long documents |
| GLM 4.5 Air Z.ai | Q2_K | offload | 54.8 GB | – | 4tok/sest. | 642 tok/s | – |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q4_K_M | offload | 47.8 GB | – | 24tok/sest. | 5966 tok/s | chat, coding, agents, long documents |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | UD-Q6_K_XL | offload | 34.1 GB | – | 68tok/sest. | 9700 tok/s | chat, coding, agents, long documents |
| Qwen3 32B Alibaba Qwen | Q4_K_M | offload | 35.5 GB | 40k | 9tok/sest. | 651 tok/s | chat, coding |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q4_K_M | offload | 35.6 GB | 47k88k with q8 cache | 9tok/sest. | 804 tok/s | chat, coding |
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | won't run | 96.6 GB | – | – | – | – |
| GLM 5.3 Flash Z.ai | UD-Q2_K_XL | won't run | 103.1 GB | – | – | – | – |
| Qwen 3.8 Flash Next Alibaba Qwen | UD-Q2_K_XL | won't run | 76.1 GB | – | – | – | – |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | won't run | 86.7 GB | – | – | – | – |
| gpt-oss 120B OpenAI | MXFP4 | won't run | 62.4 GB | – | – | – | – |
| Llama 3.3 70B Meta | Q4_K_M | won't run | 60.7 GB | – | – | – | – |
Specifications
From the manufacturer's published specifications; sources are linked where we have them.
- GPU
- GeForce RTX 5090
- Memory
- 32 GB GDDR7
- Memory bus
- 512-bit
- Memory bandwidth
- 1,792 GB/s
- FP16 compute
- 209 TFLOPS
- Software
- CUDA
- Board power
- 575 W
- PCIe generation
- Gen 5
- PCIe lanes
- x16