NVIDIA GeForce RTX 5080
16 GB · 960 GB/s · 360 W
Prices
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What two of them run
Every model in the catalogue, with the best quant for this hardware. Estimates, not measurements.
| Model | Quant | Fits | Memory | Max context | Decode @32k | Prefill | Good for |
|---|---|---|---|---|---|---|---|
| Qwen 3.8 27B Alibaba Qwen | Q8_0 | fits | 30.5 GB | 36k64k with q8 cache | 19tok/sest. | 820 tok/s | chat |
| Qwen 3.6 27B Alibaba Qwen | Q8_0 | fits | 30.1 GB | 42k74k with q8 cache | 19tok/sest. | 820 tok/s | chat |
| Gemma 4 31B | Q6_K | fits | 28.0 GB | 64k122k with q8 cache | 21tok/sest. | 731 tok/s | chat, coding |
| Qwen 3.6 35B-A3B Alibaba Qwen | UD-Q6_K | fits | 29.3 GB | 92k144k with q8 cache | 112tok/sest. | 5855 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 27B Alibaba Qwen | Q8_0 | fits | 30.1 GB | 42k74k with q8 cache | 19tok/sest. | 820 tok/s | chat |
| Gemma 4 26B-A4B | Q8_0 | fits | 27.1 GB | 176k256k with q8 cache | 71tok/sest. | 5209 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q6_K | fits | 28.8 GB | 109k170k with q8 cache | 114tok/sest. | 5855 tok/s | chat, coding, agents, long documents |
| GLM 4.7 Flash Z.ai | Q6_K | fits | 25.9 GB | 116k198k with q8 cache | 61tok/sest. | 3057 tok/s | chat, coding, agents, long documents |
| Devstral Small 2 24B Mistral AI | Q8_0 | fits | 29.6 GB | 39k71k with q8 cache | 20tok/sest. | 865 tok/s | chat |
| Kimi Linear 48B-A3B Moonshot AI | Q4_K_M | fits | 29.6 GB | 122k167k with q8 cache | 167tok/sest. | 5046 tok/s | chat, coding, long documents |
| gpt-oss 20B OpenAI | MXFP4 | fits | 13.3 GB | 128k | 110tok/sest. | 4371 tok/s | chat, coding, agents, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q6_K | fits | 27.7 GB | 63k113k with q8 cache | 63tok/sest. | 2693 tok/s | chat, coding, agents |
| Qwen3 32B Alibaba Qwen | Q4_K_M | fits | 27.7 GB | 40k | 21tok/sest. | 509 tok/s | chat, coding |
| Gemma 4 12B | Q8_0 | fits | 13.9 GB | 256k | 44tok/sest. | 1902 tok/s | chat, coding, long documents |
| Qwen 3.5 9B Alibaba Qwen | Q8_0 | fits | 11.2 GB | 256k | 56tok/sest. | 2370 tok/s | chat, coding, long documents |
| Gemma 3 27B | Q6_K | fits | 24.8 GB | 102k128k with q8 cache | 24tok/sest. | 870 tok/s | chat, coding |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q4_K_M | fits | 27.8 GB | 43k80k with q8 cache | 21tok/sest. | 585 tok/s | chat, coding |
| Mistral Small 3.2 24B Mistral AI | Q8_0 | fits | 29.6 GB | 39k71k with q8 cache | 20tok/sest. | 865 tok/s | chat |
| Ministral 3 14B Mistral AI | Q8_0 | fits | 19.7 GB | 100k183k with q8 cache | 30tok/sest. | 1316 tok/s | chat, coding |
| Qwen3 14B Alibaba Qwen | Q8_0 | fits | 20.9 GB | 40k | 28tok/sest. | 1184 tok/s | chat, coding |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q8_0 | fits | 13.9 GB | 128k | 44tok/sest. | 1952 tok/s | chat, coding, long documents |
| Qwen3 8B Alibaba Qwen | Q8_0 | fits | 13.9 GB | 40k | 44tok/sest. | 1952 tok/s | chat, coding, long documents |
| Phi-4 14B Microsoft | Q8_0 | fits | 22.0 GB | 16k | 27tok/sest. | 1190 tok/s | chat, coding |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 6.5 GB | 256k | 106tok/sest. | 4434 tok/s | chat, coding, long documents |
| Ministral 3 8B Mistral AI | Q8_0 | fits | 13.9 GB | 153k256k with q8 cache | 44tok/sest. | 1886 tok/s | chat, coding, long documents |
| Granite 4.2 8B IBM | Q8_0 | fits | 15.0 GB | 128k | 41tok/sest. | 1796 tok/s | chat, coding, agents, long documents |
| Gemma 4 E4B | Q8_0 | fits | 9.8 GB | 128k | 65tok/sest. | 2977 tok/s | chat, coding, long documents |
| LFM2.5 8B-A1B Liquid AI | Q8_0 | fits | 11.2 GB | 125k | 134tok/sest. | 9739 tok/s | chat, coding, long documents |
| Llama 3.1 8B Meta | Q6_K | fits | 11.4 GB | 128k | 55tok/sest. | 2063 tok/s | chat, coding, long documents |
| Qwen 3.5 122B-A10B Alibaba Qwen | UD-Q2_K_XL | offload | 41.1 GB | – | 23tok/sest. | 1624 tok/s | chat, coding |
| Qwen3 Coder Next Alibaba Qwen | Q4_K_M | offload | 47.3 GB | – | 24tok/sest. | 3638 tok/s | chat, coding |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q2_K_XL | offload | 52.6 GB | – | 12tok/sest. | 1449 tok/s | – |
| Mistral Small 4 119B Mistral AI | UD-Q2_K_XL | offload | 39.4 GB | – | 35tok/sest. | 1848 tok/s | chat, coding, agents, long documents |
| GLM 4.5 Air Z.ai | Q2_K | offload | 49.2 GB | – | 6tok/sest. | 550 tok/s | – |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q4_K_M | offload | 47.3 GB | – | 29tok/sest. | 4329 tok/s | chat, coding |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | UD-Q6_K_XL | offload | 34.1 GB | – | 50tok/sest. | 6276 tok/s | chat, coding, agents, long documents |
| Llama 3.3 70B Meta | Q4_K_M | offload | 50.9 GB | – | 2tok/sest. | 209 tok/s | – |
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | won't run | 94.2 GB | – | – | – | – |
| GLM 5.3 Flash Z.ai | UD-Q2_K_XL | won't run | 103.0 GB | – | – | – | – |
| Qwen 3.8 Flash Next Alibaba Qwen | UD-Q2_K_XL | won't run | 75.6 GB | – | – | – | – |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | won't run | 79.2 GB | – | – | – | – |
| gpt-oss 120B OpenAI | MXFP4 | won't run | 61.5 GB | – | – | – | – |
Specifications
From the manufacturer's published specifications; sources are linked where we have them.
- GPU
- GeForce RTX 5080
- Memory
- 16 GB GDDR7
- Memory bus
- 256-bit
- Memory bandwidth
- 960 GB/s
- FP16 compute
- 113 TFLOPS
- Software
- CUDA
- Board power
- 360 W
- PCIe generation
- Gen 5
- PCIe lanes
- x16