NVIDIA GeForce RTX 5060
8 GB · 448 GB/s · 145 W
In short
The NVIDIA GeForce RTX 5060 has 8 GB of GDDR7 memory with 448 GB/s of bandwidth, which sets how fast it generates text. At 128k context it runs 5 of the 129 open models we track fully in memory; the most capable is Qwen2.5 0.5B at Q8_0, at about 130 tok/s (estimated). The best new price for the NVIDIA GeForce RTX 5060 in Canada is $660 at Amazon; used, it starts at $575 (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 |
|---|---|---|---|---|---|
| eBayZOTAC GAMING GeForce RTX 5060 Twin Edge OC DLSS 4 8GB GDDR7 128-bit 28 Gbps PCIE | used, asking price | $575 | In stock | 2 h ago | Buy |
| AmazonASUS Dual GeForce RTX 5060 8GB GDDR7 OC Edition | New | $660 | In stock | 4 h ago | Buy |
| AmazonMSI Gaming RTX 5060 8G Shadow 2X OC Graphics Card | New | $690 | In stock | 4 h ago | Buy |
| AmazonGIGABYTE GeForce RTX 5060 WINDFORCE OC 8G Graphics Card | New | $710 | In stock | 4 h ago | Buy |
| AmazonASUS Dual GeForce RTX 5060 8GB GDDR7 White OC Edition Gaming Graphics Card | New | $720 | In stock | 4 h ago | Buy |
| AmazonZOTAC Gaming GeForce RTX 5060 Twin Edge OC DLSS 4 8GB GDDR7 128-bit 28 Gbps… | New | $728 | In stock | 4 h ago | Buy |
| AmazonASUS PRIME GeForce RTX 5060 8GB GDDR7 Gaming Graphics Card | New | $740 | In stock | 4 h ago | Buy |
| AmazonASUS The SFF-Ready Prime GeForce RTX 5060 8GB GDDR7 OC Edition Graphics Card | New | $740 | In stock | 4 h ago | Buy |
| AmazonMSI Gaming RTX 5060 8G Ventus 2X OC Graphics Card | New | $745 | In stock | 4 h ago | Buy |
| AmazonASUS GeForce RTX 5060 LP BRK 8GB GDDR7 OC Edition Graphics Card | New | $752 | In stock | 10 h ago | Buy |
| AmazonMSI Gaming RTX 5060 8G Ventus 3X OC Graphics Card | New | $770 | In stock | 4 h ago | Buy |
| AmazonMSI Gaming RTX 5060 8G Gaming Trio OC Graphics Card | New | $775 | In stock | 4 h ago | Buy |
| AmazonMSI Gaming RTX 5060 8G Gaming OC Graphics Card | New | $780 | In stock | 4 h ago | Buy |
| AmazonASUS TUF Gaming GeForce RTX 5060 8GB GDDR7 OC Edition Gaming Graphics Card | New | $800 | In stock | 4 h ago | Buy |
| eBayMSI GeForce RTX 5060 8G VENTUS 2X OC 8GB GDDR7 Graphics Card | New | $975 | 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 @128k | Prefill | Good for |
|---|---|---|---|---|---|---|---|
| Qwen2.5 0.5B Alibaba Qwen | Q8_0 | fits | 3.4 GB | 32k | 130tok/sest. | 1303 tok/s | chat, coding, long documents |
| Qwen3.5 0.8B Alibaba Qwen | Q8_0 | fits | 3.7 GB | 256k | 114tok/sest. | 1737 tok/s | chat, coding, agents, long documents |
| Qwen3.5 2B Alibaba Qwen | Q5_K_M | fits | 4.3 GB | 256k | 91tok/sest. | 1111 tok/s | chat, coding, agents, long documents |
| LFM3 1.7B Liquid AI | Q8_0 | fits | 4.7 GB | 256k | 80tok/sest. | 1285 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 1.5B DeepSeek | Q8_0 | fits | 6.7 GB | 128k | 49tok/sest. | 582 tok/s | chat, coding, long documents |
| Qwen 3.8 27B Alibaba Qwen | UD-Q4_K_M | offload | 24.9 GB | – | 3tok/sest. | 59 tok/s | – |
| Qwen 3.6 27B Alibaba Qwen | Q4_K_M | offload | 25.3 GB | – | 3tok/sest. | 58 tok/s | – |
| Gemma 4 31B | Q4_K_M | offload | 29.3 GB | – | 2tok/sest. | 53 tok/s | – |
| Qwen 3.6 35B-A3B Alibaba Qwen | MXFP4 | offload | 24.2 GB | – | 9tok/sest. | 287 tok/s | chat |
| Qwen 3.5 27B Alibaba Qwen | Q4_K_M | offload | 25.2 GB | – | 3tok/sest. | 58 tok/s | – |
| Gemma 4 26B-A4B | MXFP4 | offload | 19.6 GB | – | 8tok/sest. | 374 tok/s | chat |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q4_K_M | offload | 24.5 GB | – | 9tok/sest. | 286 tok/s | chat |
| GLM 4.7 Flash Z.ai | Q4_K_M | offload | 25.1 GB | – | 4tok/sest. | 134 tok/s | – |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | MXFP4 | offload | 23.9 GB | – | 13tok/sest. | 388 tok/s | chat |
| Kimi Linear 48B-A3B Moonshot AI | Q4_K_M | offload | 30.5 GB | – | 13tok/sest. | 202 tok/s | chat |
| gpt-oss 20B OpenAI | Q4_K_M | offload | 15.3 GB | – | 9tok/sest. | 267 tok/s | chat |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q4_K_M | offload | 30.7 GB | – | 3tok/sest. | 78 tok/s | chat |
| Gemma 4 12B | Q4_K_M | offload | 10.4 GB | – | 12tok/sest. | 208 tok/s | chat, coding |
| Qwen 3.5 9B Alibaba Qwen | Q4_K_M | offload | 10.8 GB | 36k60k with q8 cache | 11tok/sest. | 242 tok/s | chat, coding |
| Gemma 3 27B | Q4_K_M | offload | 27.3 GB | – | 2tok/sest. | 70 tok/s | – |
| Ministral 3 14B Mistral AI | Q4_K_M | offload | 29.1 GB | – | 2tok/sest. | 64 tok/s | – |
| Qwen3 14B Alibaba Qwen | Q4_K_M | offload | 29.8 GB | – | 2tok/sest. | 55 tok/s | – |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q4_K_M | offload | 24.1 GB | 13k25k with q8 cache | 3tok/sest. | 87 tok/s | chat |
| Qwen3 8B Alibaba Qwen | Q4_K_M | offload | 24.1 GB | 13k25k with q8 cache | 3tok/sest. | 87 tok/s | chat |
| Qwen 3.5 4B Alibaba Qwen | Q4_K_M | offload | 8.0 GB | 110k182k with q8 cache | 28tok/sest. | 453 tok/s | chat, coding, long documents |
| Ministral 3 8B Mistral AI | Q4_K_M | offload | 23.3 GB | 13k24k with q8 cache | 3tok/sest. | 90 tok/s | chat |
| Granite 4.2 8B IBM | Q4_K_M | offload | 26.6 GB | 9k17k with q8 cache | 3tok/sest. | 77 tok/s | chat |
| Gemma 4 E4B | Q4_K_M | offload | 9.6 GB | 61k100k with q8 cache | 15tok/sest. | 363 tok/s | chat, coding |
| LFM2.5 8B-A1B Liquid AI | UD-Q4_K_M | offload | 12.4 GB | 33k56k with q8 cache | 8tok/sest. | 421 tok/s | chat, coding |
| Llama 3.1 8B Meta | Q4_K_M | offload | 22.0 GB | 16k29k with q8 cache | 3tok/sest. | 98 tok/s | chat |
| FrogNano 4B 2609 Microsoft | Q4_K_M | offload | 8.1 GB | 109k180k with q8 cache | 27tok/sest. | 451 tok/s | chat, coding, agents, long documents |
| MiniCPM5 2B openbmb | Q4_K_M | offload | 8.2 GB | 110k128k with q8 cache | 26tok/sest. | 291 tok/s | chat, coding, agents |
| Spark X2.5 4B XHToken | mlx-4bit | offload | 8.8 GB | 93k156k with q8 cache | 19tok/sest. | 421 tok/s | chat, coding, agents, long documents |
| Mellum2.1 12B A2.5B Thinking JetBrains | Q4_K_M | offload | 11.5 GB | – | 17tok/sest. | 508 tok/s | chat, coding, agents, long documents |
| LFM2.5 2.6B Liquid AI | Q4_K_M | offload | 10.5 GB | 79k128k with q8 cache | 12tok/sest. | 319 tok/s | chat, coding, agents |
| LFM2.5 VL 3B Liquid AI | Q4_K_M | offload | 10.5 GB | 32k | 12tok/sest. | 307 tok/s | chat, coding, agents |
| GLM 4.6V Flash Z.ai | Q4_K_M | offload | 12.2 GB | 21k35k with q8 cache | 8tok/sest. | 100 tok/s | chat, coding |
| Kimi VL A3B Thinking 2506 Moonshot AI | Q4_K_M | offload | 15.1 GB | – | 8tok/sest. | 279 tok/s | chat, coding |
| DeepSeek R1 Distill Qwen 7B DeepSeek | Q4_K_M | offload | 12.8 GB | 38k66k with q8 cache | 8tok/sest. | 148 tok/s | chat, coding |
| Kimi VL A3B Moonshot AI | mlx-5bit | offload | 16.3 GB | – | 8tok/sest. | 199 tok/s | chat |
| GLM 4 9B 0414 Z.ai | mlx-4bit | offload | 13.0 GB | 2k4k with q8 cache | 7tok/sest. | 99 tok/s | chat |
| granite vision 4.1 4b IBM | Q4_K_M | offload | 13.4 GB | 56k100k with q8 cache | 7tok/sest. | 173 tok/s | chat, coding |
| granite 4.2 3b IBM | Q4_K_M | offload | 13.6 GB | 54k95k with q8 cache | 7tok/sest. | 175 tok/s | chat, coding, agents |
| Ministral 3 3B Instruct 2512 Mistral AI | Q4_K_M | offload | 16.4 GB | 43k78k with q8 cache | 5tok/sest. | 155 tok/s | chat, coding, agents |
| GLM 4.1V 9B Thinking Z.ai | mlx-8bit | offload | 17.4 GB | – | 5tok/sest. | 85 tok/s | – |
| Muse Glimmer 30B meta-models | Q4_K_M | offload | 19.3 GB | – | 4tok/sest. | 69 tok/s | – |
| LFM2.5 24B A2B Liquid AI | Q4_K_M | offload | 25.7 GB | – | 3tok/sest. | 185 tok/s | chat |
| DeepSeek R1 Distill Llama 8B DeepSeek | Q4_K_M | offload | 22.0 GB | 16k29k with q8 cache | 3tok/sest. | 98 tok/s | chat |
| Ministral 3 8B Reasoning 2512 Mistral AI | Q4_K_M | offload | 23.3 GB | 13k24k with q8 cache | 3tok/sest. | 90 tok/s | chat |
| Ministral 3 14B Reasoning 2512 Mistral AI | Q4_K_M | offload | 29.1 GB | – | 2tok/sest. | 64 tok/s | – |
| Qwen3.8 27B OBLITERATED OBLITERATUS | mlx-4bit | offload | 28.8 GB | – | 2tok/sest. | 56 tok/s | – |
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | won't run | 102.4 GB | – | – | – | – |
| GLM 5.3 Flash Z.ai | UD-Q2_K_XL | won't run | 104.2 GB | – | – | – | – |
| Qwen 3.8 Flash Next Alibaba Qwen | UD-Q2_K_XL | won't run | 78.0 GB | – | – | – | – |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | won't run | 102.6 GB | – | – | – | – |
| Qwen 3.5 122B-A10B Alibaba Qwen | UD-Q2_K_XL | won't run | 43.6 GB | – | – | – | – |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q2_K_XL | won't run | 53.5 GB | – | – | – | – |
| Qwen3 Coder Next Alibaba Qwen | Q4_K_M | won't run | 49.7 GB | – | – | – | – |
| gpt-oss 120B OpenAI | Q4_K_M | won't run | 64.4 GB | – | – | – | – |
| Mistral Small 4 119B Mistral AI | UD-Q2_K_XL | won't run | 41.7 GB | – | – | – | – |
| GLM 4.5 Air Z.ai | Q2_K | won't run | 66.7 GB | – | – | – | – |
| Devstral Small 2 24B Mistral AI | Q4_K_M | won't run | 34.8 GB | – | – | – | – |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q4_K_M | won't run | 49.7 GB | – | – | – | – |
| Qwen3 32B Alibaba Qwen | Q4_K_M | won't run | 51.9 GB | – | – | – | – |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q4_K_M | won't run | 51.9 GB | – | – | – | – |
| Llama 3.3 70B Meta | Q4_K_M | won't run | 81.1 GB | – | – | – | – |
| Mistral Small 3.2 24B Mistral AI | Q4_K_M | won't run | 34.8 GB | – | – | – | – |
| Phi-4 14B Microsoft | Q4_K_M | won't run | 34.7 GB | – | – | – | – |
| DeepSeek R1 DeepSeek | Q4_K_M | won't run | 386.7 GB | – | – | – | – |
| DeepSeek R1 0528 DeepSeek | Q4_K_M | won't run | 387.2 GB | – | – | – | – |
| DeepSeek R1 Distill Llama 70B DeepSeek | Q4_K_M | won't run | 81.1 GB | – | – | – | – |
| DeepSeek R1 Distill Qwen 14B DeepSeek | Q4_K_M | won't run | 33.8 GB | – | – | – | – |
| DeepSeek R1 Zero DeepSeek | Q4_K_M | won't run | 386.7 GB | – | – | – | – |
| DeepSeek V3 DeepSeek | Q4_K_M | won't run | 386.7 GB | – | – | – | – |
| DeepSeek V3 0324 DeepSeek | Q4_K_M | won't run | 386.7 GB | – | – | – | – |
| DeepSeek V3.1 DeepSeek | Q4_K_M | won't run | 387.6 GB | – | – | – | – |
| DeepSeek V3.1 Terminus DeepSeek | Q4_K_M | won't run | 387.6 GB | – | – | – | – |
| DeepSeek V3.2 DeepSeek | Q4_K_M | won't run | 387.6 GB | – | – | – | – |
| DeepSeek V4 Flash 0731 DeepSeek | MXFP4 | won't run | 157.8 GB | – | – | – | – |
| DeepSeek V4 Flash Vision Exp DeepSeek | MXFP4 | won't run | 166.6 GB | – | – | – | – |
| Devstral 2 123B Instruct 2512 Mistral AI | Q4_K_M | won't run | 115.2 GB | – | – | – | – |
| Devstral Small 2507 Mistral AI | Q4_K_M | won't run | 34.8 GB | – | – | – | – |
| GLM 4.5 Z.ai | Q4_K_M | won't run | 249.0 GB | – | – | – | – |
| GLM 4.5V Z.ai | Q4_K_M | won't run | 83.7 GB | – | – | – | – |
| GLM 4.6 Z.ai | Q4_K_M | won't run | 248.2 GB | – | – | – | – |
| GLM 4.6V Z.ai | Q4_K_M | won't run | 90.1 GB | – | – | – | – |
| GLM 4.7 Z.ai | Q4_K_M | won't run | 249.0 GB | – | – | – | – |
| GLM 5 Z.ai | MXFP4 | won't run | 394.8 GB | – | – | – | – |
| GLM 5.1 Z.ai | MXFP4 | won't run | 432.4 GB | – | – | – | – |
| GLM 5.2 Z.ai | UD-Q4_K_M | won't run | 446.3 GB | – | – | – | – |
| GLM 5.3 Z.ai | Q8_0 | won't run | 758.7 GB | – | – | – | – |
| Kimi Dev 72B Moonshot AI | Q6_K | won't run | 101.4 GB | – | – | – | – |
| Kimi K2 Moonshot AI | Q4_K_M | won't run | 588.2 GB | – | – | – | – |
| Kimi K2 Instruct 0905 Moonshot AI | Q4_K_M | won't run | 588.6 GB | – | – | – | – |
| Kimi K2 Thinking Moonshot AI | Q4_K_M | won't run | 588.6 GB | – | – | – | – |
| Kimi K2.5 Moonshot AI | Q4_K_M | won't run | 588.6 GB | – | – | – | – |
| Magistral Small 2506 Mistral AI | Q4_K_M | won't run | 34.8 GB | – | – | – | – |
| Magistral Small 2507 Mistral AI | Q4_K_M | won't run | 34.8 GB | – | – | – | – |
| Magistral Small 2509 Mistral AI | Q4_K_M | won't run | 34.8 GB | – | – | – | – |
| MiniMax M2 MiniMax | Q4_K_M | won't run | 161.3 GB | – | – | – | – |
| MiniMax M2.1 MiniMax | Q4_K_M | won't run | 161.3 GB | – | – | – | – |
| MiniMax M2.5 MiniMax | MXFP4 | won't run | 147.7 GB | – | – | – | – |
| MiniMax M3 MiniMax | MXFP4 | won't run | 256.1 GB | – | – | – | – |
| Mistral Medium 3.5 128B Mistral AI | Q4_K_M | won't run | 115.2 GB | – | – | – | – |
| granite 4.2 30b IBM | Q4_K_M | won't run | 50.2 GB | – | – | – | – |
Specifications
From the manufacturer's published specifications; sources are linked where we have them.
- GPU
- GeForce RTX 5060
- Memory
- 8 GB GDDR7
- Memory bus
- 128-bit
- Memory bandwidth
- 448 GB/s
- FP16 compute
- 19.177 TFLOPS
- Software
- CUDA
- Board power
- 145 W
- PCIe generation
- Gen 5
- PCIe lanes
- x8
Compare with
Questions
- How much memory does the NVIDIA GeForce RTX 5060 have for AI models?
- The NVIDIA GeForce RTX 5060 has 8 GB of GDDR7 memory with 448 GB/s of bandwidth, which sets how fast it generates text.
- What is the best model the NVIDIA GeForce RTX 5060 can run locally?
- Qwen2.5 0.5B (Q8_0) fits fully in its memory at 128k context and generates at about 130 tok/s, an estimate from its memory bandwidth. 5 of the 129 models we track fit at that context.
- Can the NVIDIA GeForce RTX 5060 run DeepSeek V4 Flash?
- No: even at UD-Q2_K_XL, DeepSeek V4 Flash needs about 102 GB at 128k context, more than the NVIDIA GeForce RTX 5060 and system RAM can hold.
- How much does the NVIDIA GeForce RTX 5060 cost in Canada?
- The best new price for the NVIDIA GeForce RTX 5060 in Canada is $660 at Amazon; used, it starts at $575 (asking price).
Speeds on this page are for 128k context. See the best hardware for local AI at every budget.