NVIDIA GeForce RTX 4080 Super
16 GB · 736 GB/s · 320 W
Prices
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No retailer in this market lists it right now.
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 |
|---|---|---|---|---|---|---|---|
| gpt-oss 20B OpenAI | MXFP4 | fits | 13.9 GB | 116k128k with q8 cache | 68tok/sest. | 3151 tok/s | chat, coding, agents, long documents |
| Gemma 4 12B | Q8_0 | fits | 14.2 GB | 120k193k with q8 cache | 32tok/sest. | 1620 tok/s | chat, coding, long documents |
| Qwen 3.5 9B Alibaba Qwen | Q8_0 | fits | 12.0 GB | 155k256k with q8 cache | 39tok/sest. | 1983 tok/s | chat, coding, long documents |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q4_K_M | fits | 14.8 GB | 68k124k with q8 cache | 31tok/sest. | 1311 tok/s | chat, coding |
| Qwen3 8B Alibaba Qwen | Q4_K_M | fits | 14.8 GB | 40k | 31tok/sest. | 1311 tok/s | chat, coding |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 7.3 GB | 256k | 68tok/sest. | 3438 tok/s | chat, coding, long documents |
| Ministral 3 8B Mistral AI | Q5_K_M | fits | 15.2 GB | 65k118k with q8 cache | 30tok/sest. | 1297 tok/s | chat, coding |
| Gemma 4 E4B | Q8_0 | fits | 10.5 GB | 128k | 45tok/sest. | 2597 tok/s | chat, coding, long documents |
| LFM2.5 8B-A1B Liquid AI | Q8_0 | fits | 12.5 GB | 119k125k with q8 cache | 64tok/sest. | 5543 tok/s | chat, coding, long documents |
| Llama 3.1 8B Meta | Q6_K | fits | 15.2 GB | 65k118k with q8 cache | 30tok/sest. | 1408 tok/s | chat, coding |
| Qwen 3.8 27B Alibaba Qwen | UD-Q4_K_M | offload | 20.5 GB | – | 7tok/sest. | 575 tok/s | chat |
| Qwen 3.6 27B Alibaba Qwen | Q4_K_M | offload | 20.9 GB | – | 7tok/sest. | 570 tok/s | – |
| Gemma 4 31B | Q4_K_M | offload | 23.9 GB | – | 5tok/sest. | 485 tok/s | – |
| Mistral Small 4 119B Mistral AI | UD-Q2_K_XL | offload | 39.9 GB | – | 12tok/sest. | 869 tok/s | chat |
| Qwen 3.6 35B-A3B Alibaba Qwen | UD-Q4_K_M | offload | 23.0 GB | – | 23tok/sest. | 3261 tok/s | chat, coding, agents |
| Qwen 3.5 27B Alibaba Qwen | Q4_K_M | offload | 20.8 GB | – | 7tok/sest. | 571 tok/s | chat |
| Gemma 4 26B-A4B | UD-Q4_K_M | offload | 18.3 GB | – | 29tok/sest. | 3789 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q4_K_M | offload | 22.9 GB | – | 24tok/sest. | 3269 tok/s | chat, coding, agents, long documents |
| GLM 4.7 Flash Z.ai | Q4_K_M | offload | 21.4 GB | – | 13tok/sest. | 1679 tok/s | chat, coding |
| Devstral Small 2 24B Mistral AI | Q4_K_M | offload | 24.4 GB | 8k15k with q8 cache | 5tok/sest. | 517 tok/s | chat |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | UD-Q6_K_XL | offload | 34.1 GB | – | 14tok/sest. | 3351 tok/s | chat |
| Kimi Linear 48B-A3B Moonshot AI | Q4_K_M | offload | 29.6 GB | – | 24tok/sest. | 2319 tok/s | chat, coding, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q4_K_M | offload | 24.4 GB | – | 9tok/sest. | 1133 tok/s | chat |
| Qwen3 32B Alibaba Qwen | Q4_K_M | offload | 35.5 GB | – | 2tok/sest. | 227 tok/s | – |
| Gemma 3 27B | Q4_K_M | offload | 21.9 GB | – | 6tok/sest. | 623 tok/s | – |
| Mistral Small 3.2 24B Mistral AI | Q4_K_M | offload | 24.4 GB | 8k15k with q8 cache | 5tok/sest. | 517 tok/s | chat |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q4_K_M | offload | 35.6 GB | – | 2tok/sest. | 280 tok/s | – |
| Ministral 3 14B Mistral AI | Q4_K_M | offload | 18.7 GB | 43k79k with q8 cache | 10tok/sest. | 840 tok/s | chat, coding |
| Qwen3 14B Alibaba Qwen | Q4_K_M | offload | 19.5 GB | 38k40k with q8 cache | 9tok/sest. | 720 tok/s | chat, coding |
| Phi-4 14B Microsoft | Q4_K_M | offload | 21.9 GB | 16k | 6tok/sest. | 678 tok/s | chat, coding |
| Granite 4.2 8B IBM | Q4_K_M | offload | 16.2 GB | 58k107k with q8 cache | 20tok/sest. | 1159 tok/s | chat, coding, agents |
| 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 | – | – | – | – |
| Qwen 3.5 122B-A10B Alibaba Qwen | UD-Q2_K_XL | won't run | 41.7 GB | – | – | – | – |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q2_K_XL | won't run | 52.6 GB | – | – | – | – |
| Qwen3 Coder Next Alibaba Qwen | Q4_K_M | won't run | 47.8 GB | – | – | – | – |
| gpt-oss 120B OpenAI | MXFP4 | won't run | 62.4 GB | – | – | – | – |
| GLM 4.5 Air Z.ai | Q2_K | won't run | 54.8 GB | – | – | – | – |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q4_K_M | won't run | 47.8 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 4080 Super
- Memory
- 16 GB GDDR6X
- Memory bus
- 256-bit
- Memory bandwidth
- 736 GB/s
- FP16 compute
- 104 TFLOPS
- Software
- CUDA
- Board power
- 320 W
- PCIe generation
- Gen 4
- PCIe lanes
- x16