NVIDIA GeForce RTX 5080
16 GB · 960 GB/s · 360 W
In short
The NVIDIA GeForce RTX 5080 has 16 GB of GDDR7 memory with 960 GB/s of bandwidth, which sets how fast it generates text. At 32k context it runs 30 of the 113 open models we track fully in memory; the most capable is gpt-oss 20B at MXFP4, at about 110 tok/s (estimated). The best new price for the NVIDIA GeForce RTX 5080 in Canada is $2,370 at Amazon; used, it starts at $2,850 (asking price).
Updated . Speeds are estimates; how they are worked out.
Prices
Every retailer we track in Canada, cheapest first. Buy links may earn us a commission.
| Retailer | Condition | Price | Stock | Checked | Buy |
|---|---|---|---|---|---|
| AmazonThe SFF-Ready ASUS Prime GeForce RTX 5080 16GB GDDR7 OC Edition Graphics Card | New | $2,370 | In stock | 1 h ago | Buy |
| AmazonASUS Prime GeForce RTX 5080 EVO 16GB GDDR7 OC Edition Gaming Graphics Card | New | $2,420 | In stock | 1 h ago | Buy |
| AmazonMSI Gaming RTX 5080 16G Ventus 3X OC White Graphics Card | New | $2,580 | In stock | 1 h ago | Buy |
| Amazonmsi Gaming RTX 5080 16G Ventus 3X OC Black Graphics Card | New | $2,640 | In stock | 1 h ago | Buy |
| AmazonASUS TUF Gaming GeForce RTX 5080 16GB GDDR7 BTF OC Edition Gaming Graphics Card | New | $2,650 | In stock | 1 h ago | Buy |
| eBayASUS TUF GAMING GeForce RTX 5080 16GB Oc New In Hand Shipping To Canada USA | New | $2,570+ $114 delivery | In stock | 2 h ago | Buy |
| AmazonASUS ProArt GeForce RTX 5080 16GB GDDR7 OC Edition Graphics Card | New | $2,700 | In stock | 1 h ago | Buy |
| AmazonGigabyte GeForce RTX 5080 Gaming OC 16G Graphics Card | New | $2,718 | In stock | 1 h ago | Buy |
| Amazonmsi Gaming RTX 5080 16G Inspire 3X OC Black Graphics Card | New | $2,720 | In stock | 1 h ago | Buy |
| eBayNEW Gigabyte RTX 5080 WINDFORCE SFF 16GB GDDR7 SFF-Ready | New | $2,700+ $30 delivery | In stock | 2 h ago | Buy |
| AmazonMSI Gaming RTX 5080 16G Gaming Trio OC White Graphics Card | New | $2,750 | In stock | 1 h ago | Buy |
| eBayASUS ROG Astral RTX 5080 16GB GDDR7 In White | New | $2,750 | In stock | 2 h ago | Buy |
| AmazonPNY NVIDIA GeForce RTX 5080 Slim Dual-Fan Dual-Slot OC Graphics Card | New | $2,763 | In stock | 1 h ago | Buy |
| eBayNVIDIA GeForce RTX 5080 16GB GDDR7 Founders Edition | used, asking price | $2,850 | In stock | 2 h ago | Buy |
| AmazonASUS ROG Astral GeForce RTX 5080 16GB GDDR7 OC Edition Gaming Graphics Card | New | $2,920 | In stock | 1 h ago | Buy |
| AmazonAsus Prime GeForce RTX 5080 16GB GDDR7 Prime-RTX5080-16G Pci-Express 5.0 Dlss… | New | $2,940 | In stock | 1 h ago | Buy |
| AmazonMSI Gaming RTX 5080 16G SUPRIM Liquid SOC Graphics Card | New | $2,950 | In stock | 1 h ago | Buy |
| eBayAORUS Master RTX 5080 Graphics Card | New | $2,999 | In stock | 2 h ago | Buy |
| AmazonGIGABYTE AORUS GeForce RTX 5080 Master ICE 16G Graphics Card | New | $3,000 | In stock | 1 h ago | Buy |
| eBayAsus ROG Astral GeForce RTX 5080 16GB GDDR7 OC Edition | New | $3,000 | In stock | 2 h ago | Buy |
| AmazonASUS ROG Astral GeForce RTX 5080 16GB GDDR7 White OC Edition Graphics Card | New | $3,060 | In stock | 1 h ago | Buy |
| eBayASUS PRIME GeForce RTX 5080 OC 16GB / Gaming Graphics Card | New | $3,100+ $160 delivery | In stock | 2 h ago | Buy |
| eBayMSI GeForce RTX 5080 Gaming Trio OC 16GB GDDR7 Video Card | New | $3,500+ $60 delivery | In stock | 2 h ago | Buy |
| eBayASUS TUF GAMING GeForce RTX 5080 16GB Oc New In Hand Shipping To Canada + USA | New | $3,700 | In stock | 2 h ago | Buy |
| eBayAsus ROG Astral GeForce RTX 5080 16GB GDDR7 OC HATSUNE MIKU EDITION | New | $7,000 | In stock | 2 h ago | Buy |
Price history
Lowest price shown each day over the last 90 days.
Not enough price history yet.
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 @32k | Prefill | Good for |
|---|---|---|---|---|---|---|---|
| gpt-oss 20B OpenAI | MXFP4 | fits | 12.9 GB | 116k128k with q8 cache | 110tok/sest. | 4371 tok/s | chat, coding, agents, long documents |
| Gemma 4 12B | Q8_0 | fits | 13.5 GB | 120k193k with q8 cache | 44tok/sest. | 1902 tok/s | chat, coding, long documents |
| Qwen 3.5 9B Alibaba Qwen | Q8_0 | fits | 10.8 GB | 155k256k with q8 cache | 56tok/sest. | 2370 tok/s | chat, coding, long documents |
| Qwen3 14B Alibaba Qwen | Q4_K_M | fits | 14.3 GB | 38k40k with q8 cache | 41tok/sest. | 1184 tok/s | chat, coding |
| Ministral 3 14B Mistral AI | Q5_K_M | fits | 14.8 GB | 35k64k with q8 cache | 40tok/sest. | 1316 tok/s | chat, coding |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q8_0 | fits | 13.5 GB | 44k81k with q8 cache | 44tok/sest. | 1952 tok/s | chat, coding |
| Qwen3 8B Alibaba Qwen | Q8_0 | fits | 13.5 GB | 40k | 44tok/sest. | 1952 tok/s | chat, coding |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 6.1 GB | 256k | 106tok/sest. | 4434 tok/s | chat, coding, long documents |
| Ministral 3 8B Mistral AI | Q8_0 | fits | 13.5 GB | 45k82k with q8 cache | 44tok/sest. | 1886 tok/s | chat, coding |
| Granite 4.2 8B IBM | Q8_0 | fits | 14.6 GB | 36k67k with q8 cache | 41tok/sest. | 1796 tok/s | chat, coding, agents |
| Gemma 4 E4B | Q8_0 | fits | 9.4 GB | 128k | 65tok/sest. | 2977 tok/s | chat, coding, long documents |
| LFM2.5 8B-A1B Liquid AI | Q8_0 | fits | 10.8 GB | 119k125k with q8 cache | 134tok/sest. | 9739 tok/s | chat, coding, long documents |
| Llama 3.1 8B Meta | Q6_K | fits | 11.0 GB | 65k118k with q8 cache | 55tok/sest. | 2063 tok/s | chat, coding |
| Qwen2.5 0.5B Alibaba Qwen | Q8_0 | fits | 1.8 GB | 32k | 637tok/sest. | 21211 tok/s | chat, coding, long documents |
| Qwen3.5 0.8B Alibaba Qwen | Q8_0 | fits | 2.0 GB | 256k | 483tok/sest. | 19924 tok/s | chat, coding, agents, long documents |
| Qwen3.5 2B Alibaba Qwen | Q5_K_M | fits | 2.6 GB | 256k | 321tok/sest. | 9499 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 1.5B DeepSeek | Q8_0 | fits | 3.5 GB | 128k | 210tok/sest. | 7979 tok/s | chat, coding, long documents |
| MiniCPM5 2B openbmb | Q8_0 | fits | 4.7 GB | 128k | 146tok/sest. | 4765 tok/s | chat, coding, agents, long documents |
| LFM2.5 2.6B Liquid AI | Q8_0 | fits | 5.4 GB | 128k | 122tok/sest. | 5398 tok/s | chat, coding, agents, long documents |
| LFM2.5 VL 3B Liquid AI | Q8_0 | fits | 5.4 GB | 32k | 122tok/sest. | 4950 tok/s | chat, coding, agents, long documents |
| Mellum2.1 12B A2.5B Thinking JetBrains | Q8_0 | fits | 13.4 GB | 128k | 113tok/sest. | 7032 tok/s | chat, coding, agents, long documents |
| Kimi VL A3B Moonshot AI | mlx-6bit | fits | 14.7 GB | 51k84k with q8 cache | 101tok/sest. | 5284 tok/s | chat, coding, agents, long documents |
| granite vision 4.1 4b IBM | Q8_0 | fits | 6.8 GB | 128k | 94tok/sest. | 3458 tok/s | chat, coding, long documents |
| granite 4.2 3b IBM | Q8_0 | fits | 7.0 GB | 128k | 91tok/sest. | 3624 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 7B DeepSeek | Q8_0 | fits | 10.2 GB | 118k128k with q8 cache | 60tok/sest. | 2332 tok/s | chat, coding, long documents |
| GLM 4.6V Flash Z.ai | Q8_0 | fits | 11.5 GB | 119k128k with q8 cache | 53tok/sest. | 1623 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Llama 8B DeepSeek | Q8_0 | fits | 12.8 GB | 51k93k with q8 cache | 46tok/sest. | 2063 tok/s | chat, coding |
| GLM 4.1V 9B Thinking Z.ai | mlx-8bit | fits | 13.1 GB | 64k | 45tok/sest. | 1623 tok/s | chat, coding, long documents |
| Ministral 3 8B Reasoning 2512 Mistral AI | Q8_0 | fits | 13.5 GB | 45k82k with q8 cache | 44tok/sest. | 1886 tok/s | chat, coding, agents |
| DeepSeek R1 Distill Qwen 14B DeepSeek | Q4_K_M | fits | 15.3 GB | 32k60k with q8 cache | 39tok/sest. | 1114 tok/s | chat, coding |
| Qwen 3.8 27B Alibaba Qwen | UD-Q4_K_M | offload | 18.4 GB | – | 12tok/sest. | 737 tok/s | chat |
| Qwen 3.5 122B-A10B Alibaba Qwen | UD-Q2_K_XL | offload | 40.7 GB | – | 11tok/sest. | 1189 tok/s | – |
| Qwen 3.6 27B Alibaba Qwen | Q4_K_M | offload | 18.7 GB | – | 11tok/sest. | 729 tok/s | chat |
| Gemma 4 31B | Q4_K_M | offload | 21.2 GB | – | 7tok/sest. | 605 tok/s | – |
| Mistral Small 4 119B Mistral AI | UD-Q2_K_XL | offload | 39.0 GB | – | 16tok/sest. | 1343 tok/s | chat |
| Qwen 3.6 35B-A3B Alibaba Qwen | MXFP4 | offload | 21.8 GB | – | 34tok/sest. | 4782 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 27B Alibaba Qwen | Q4_K_M | offload | 18.6 GB | – | 11tok/sest. | 731 tok/s | chat |
| Gemma 4 26B-A4B | UD-Q4_K_M | offload | 17.5 GB | – | 45tok/sest. | 4816 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q4_K_M | offload | 22.1 GB | – | 33tok/sest. | 4749 tok/s | chat, coding, agents, long documents |
| GLM 4.7 Flash Z.ai | Q4_K_M | offload | 19.6 GB | – | 23tok/sest. | 2646 tok/s | chat, coding |
| Devstral Small 2 24B Mistral AI | Q4_K_M | offload | 19.2 GB | 8k15k with q8 cache | 10tok/sest. | 757 tok/s | chat |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | UD-Q6_K_XL | offload | 33.7 GB | – | 15tok/sest. | 4445 tok/s | chat |
| Kimi Linear 48B-A3B Moonshot AI | Q4_K_M | offload | 29.2 GB | – | 28tok/sest. | 3572 tok/s | chat, coding, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q4_K_M | offload | 21.2 GB | – | 18tok/sest. | 2233 tok/s | chat |
| Qwen3 32B Alibaba Qwen | Q4_K_M | offload | 27.3 GB | – | 4tok/sest. | 372 tok/s | – |
| Gemma 3 27B | Q4_K_M | offload | 19.2 GB | – | 10tok/sest. | 762 tok/s | chat |
| Mistral Small 3.2 24B Mistral AI | Q4_K_M | offload | 19.2 GB | 8k15k with q8 cache | 10tok/sest. | 757 tok/s | chat |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q4_K_M | offload | 27.4 GB | – | 4tok/sest. | 426 tok/s | – |
| Phi-4 14B Microsoft | Q4_K_M | offload | 15.4 GB | 16k | 38tok/sest. | 1189 tok/s | chat, coding |
| LFM2.5 24B A2B Liquid AI | Q4_K_M | offload | 17.7 GB | 4k8k with q8 cache | 38tok/sest. | 4985 tok/s | chat, coding, agents |
| Devstral Small 2507 Mistral AI | Q4_K_M | offload | 19.2 GB | 8k15k with q8 cache | 10tok/sest. | 768 tok/s | chat |
| Magistral Small 2506 Mistral AI | Q4_K_M | offload | 19.2 GB | 8k15k with q8 cache | 10tok/sest. | 768 tok/s | chat |
| Magistral Small 2507 Mistral AI | Q4_K_M | offload | 19.2 GB | 8k15k with q8 cache | 10tok/sest. | 768 tok/s | chat |
| Magistral Small 2509 Mistral AI | Q4_K_M | offload | 19.2 GB | 8k15k with q8 cache | 10tok/sest. | 757 tok/s | chat |
| granite 4.2 30b IBM | Q4_K_M | offload | 25.7 GB | – | 4tok/sest. | 504 tok/s | – |
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | won't run | 93.8 GB | – | – | – | – |
| GLM 5.3 Flash Z.ai | UD-Q2_K_XL | won't run | 102.6 GB | – | – | – | – |
| Qwen 3.8 Flash Next Alibaba Qwen | UD-Q2_K_XL | won't run | 75.2 GB | – | – | – | – |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | won't run | 78.8 GB | – | – | – | – |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q2_K_XL | won't run | 52.2 GB | – | – | – | – |
| Qwen3 Coder Next Alibaba Qwen | Q4_K_M | won't run | 46.9 GB | – | – | – | – |
| gpt-oss 120B OpenAI | Q4_K_M | won't run | 60.5 GB | – | – | – | – |
| GLM 4.5 Air Z.ai | Q2_K | won't run | 48.8 GB | – | – | – | – |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q4_K_M | won't run | 46.9 GB | – | – | – | – |
| Llama 3.3 70B Meta | Q4_K_M | won't run | 50.5 GB | – | – | – | – |
| DeepSeek R1 DeepSeek | Q4_K_M | won't run | 379.7 GB | – | – | – | – |
| DeepSeek R1 0528 DeepSeek | Q4_K_M | won't run | 380.2 GB | – | – | – | – |
| DeepSeek R1 Distill Llama 70B DeepSeek | Q4_K_M | won't run | 50.5 GB | – | – | – | – |
| DeepSeek V3 0324 DeepSeek | Q4_K_M | won't run | 379.7 GB | – | – | – | – |
| DeepSeek V3.1 DeepSeek | Q4_K_M | won't run | 380.6 GB | – | – | – | – |
| DeepSeek V3.2 DeepSeek | Q4_K_M | won't run | 380.6 GB | – | – | – | – |
| DeepSeek V4 Flash 0731 DeepSeek | MXFP4 | won't run | 149.2 GB | – | – | – | – |
| DeepSeek V4 Flash Vision Exp DeepSeek | MXFP4 | won't run | 158.0 GB | – | – | – | – |
| Devstral 2 123B Instruct 2512 Mistral AI | Q8_0 | won't run | 135.6 GB | – | – | – | – |
| GLM 4.5V Z.ai | Q4_K_M | won't run | 65.9 GB | – | – | – | – |
| GLM 4.6V Z.ai | Q4_K_M | won't run | 72.2 GB | – | – | – | – |
| GLM 4.7 Z.ai | Q4_K_M | won't run | 214.0 GB | – | – | – | – |
| GLM 5.1 Z.ai | MXFP4 | won't run | 423.6 GB | – | – | – | – |
| GLM 5.2 Z.ai | UD-Q4_K_M | won't run | 437.5 GB | – | – | – | – |
| GLM 5.3 Z.ai | Q8_0 | won't run | 750.0 GB | – | – | – | – |
| Kimi K2 Moonshot AI | Q4_K_M | won't run | 581.2 GB | – | – | – | – |
| Kimi K2 Instruct 0905 Moonshot AI | Q4_K_M | won't run | 581.6 GB | – | – | – | – |
| Kimi K2 Thinking Moonshot AI | Q4_K_M | won't run | 581.6 GB | – | – | – | – |
| Kimi K2.5 Moonshot AI | Q4_K_M | won't run | 581.6 GB | – | – | – | – |
| MiniMax M2 MiniMax | Q4_K_M | won't run | 137.5 GB | – | – | – | – |
| MiniMax M2.1 MiniMax | Q4_K_M | won't run | 137.5 GB | – | – | – | – |
| MiniMax M2.5 MiniMax | MXFP4 | won't run | 123.9 GB | – | – | – | – |
| MiniMax M3 MiniMax | UD-Q4_K_M | won't run | 251.4 GB | – | – | – | – |
| Mistral Medium 3.5 128B Mistral AI | Q4_K_M | won't run | 81.6 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
Compare with
Questions
- How much memory does the NVIDIA GeForce RTX 5080 have for AI models?
- The NVIDIA GeForce RTX 5080 has 16 GB of GDDR7 memory with 960 GB/s of bandwidth, which sets how fast it generates text.
- What is the best model the NVIDIA GeForce RTX 5080 can run locally?
- gpt-oss 20B (MXFP4) fits fully in its memory at 32k context and generates at about 110 tok/s, an estimate from its memory bandwidth. 30 of the 113 models we track fit at that context.
- Can the NVIDIA GeForce RTX 5080 run DeepSeek V4 Flash?
- No: even at UD-Q2_K_XL, DeepSeek V4 Flash needs about 94 GB at 32k context, more than the NVIDIA GeForce RTX 5080 and system RAM can hold.
- How much does the NVIDIA GeForce RTX 5080 cost in Canada?
- The best new price for the NVIDIA GeForce RTX 5080 in Canada is $2,370 at Amazon; used, it starts at $2,850 (asking price).
Speeds on this page are for 32k context. See the best hardware for local AI at every budget.