NVIDIA GeForce RTX 5060 Ti 8GB
8 GB · 448 GB/s · 180 W
In short
The NVIDIA GeForce RTX 5060 Ti 8GB has 8 GB of GDDR7 memory with 448 GB/s of bandwidth, which sets how fast it generates text. At 32k context it runs 36 of the 129 open models we track fully in memory; the most capable is gpt-oss 20B at MXFP4, at about 52 tok/s (estimated). The best new price for the NVIDIA GeForce RTX 5060 Ti 8GB in the US is $510 at eBay; used, it starts at $450 (asking price).
Updated . Speeds are estimates; how they are worked out.
Prices
Every retailer we track in the US, cheapest first. Buy links may earn us a commission.
| Retailer | Condition | Price | Stock | Checked | Buy |
|---|---|---|---|---|---|
| eBayGigabyte NVIDIA GeForce RTX 5060 Ti Windforce Overclocked Dual Fan 8GB GDDR7 | used, asking price | $450+ $13 delivery | In stock | 5 h ago | Buy |
| eBayASUS Prime NVIDIA GeForce RTX 5060 Ti 8GB | used, asking price | $475 | In stock | 5 h ago | Buy |
| eBayPNY NVIDIA GeForce RTX 5060 Ti 8GB GDDR7 PCIe 5.0 RGB Graphics Card | used, asking price | $499 | In stock | 5 h ago | Buy |
| eBayGIGABYTE Eagle GeForce RTX 5060 Ti 8GB GDDR7 | used, asking price | $480+ $20 delivery | In stock | 5 h ago | Buy |
| eBayPNY GeForce RTX 5060 Ti 8GB GDDR7 Dual Fan Graphics Card PCIe 5.0 Tested | used, asking price | $500 | In stock | 5 h ago | Buy |
| eBayMSI Gaming RTX 5060 Ti 8G Ventus 2X OC Plus Graphics Card GDDR7 | used, asking price | $510 | In stock | 5 h ago | Buy |
| eBayMSI GeForce RTX 5060 TI 8GB GDDR7 SHADOW 2X OC PLUS Video Graphics Card WARRANTY | refurbished | $518 | In stock | 5 h ago | Buy |
| eBayGigabyte NVIDIA GeForce RTX 5060 Ti Windforce Overclocked Dual Fan 8GB GDDR7 | New | $510+ $10 delivery | In stock | 5 h ago | Buy |
| eBayGigabyte GeForce RTX 5060 Ti Windforce MAX EDITION OC 8GB GV-N506TWF2MAX OC-8GD | used, asking price | $520 | In stock | 5 h ago | Buy |
| eBayZOTAC GAMING GeForce RTX 5060 Ti Twin Edge OC 8GB GDDR7 Ray Tracing | used, asking price | $475+ $45 delivery | In stock | 5 h ago | Buy |
| eBayGigabyte GeForce RTX 5060 Ti 8GB GDDR7 Graphics Card 9VN506TW8-00-G10 | used, asking price | $522 | In stock | 5 h ago | Buy |
| eBayUsed GeForce RTX 5060 Ti 8GB on eBay | used, asking price | $530 | In stock | 5 h ago | Buy |
| eBayPNY NVIDIA GeForce RTX 5060 Ti OC 8GB GDDR7 PCIe 5.0 | New | $530 | In stock | 5 h ago | Buy |
| eBayNEW MSI GeForce RTX 5060 Ti 8GB Ventus 2X OC Plus GDDR7 Gaming Graphics Card | New | $535 | In stock | 5 h ago | Buy |
| eBayMSI Gaming NVIDIA RTX 5060Ti 8gb NEW | New | $550 | In stock | 5 h ago | Buy |
| eBayNew ASUS PRIME RTX 5060 Ti OC Overclocked 8GB GDDR7 PRIME-RTX5060TI-O8G SFF | New | $552 | In stock | 5 h ago | Buy |
| eBayGIGABYTE WindForce GeForce RTX 5060 Ti 8GB GDDR7 PCI Express 5.0 x8 ATX Graphics | New | $555 | In stock | 5 h ago | Buy |
| eBayGIGABYTE Eagle GeForce RTX 5060 Ti 8GB GDDR7 PCI Express 5.0 ATX Graphics Card G | New | $555 | In stock | 5 h ago | Buy |
| eBayGIGABYTE Eagle GeForce RTX 5060 Ti 8GB GDDR7 PCI Express 5.0 x8 ATX Graphics Car | New | $565 | In stock | 5 h ago | Buy |
| eBayGIGABYTE Eagle GeForce RTX 5060 Ti 8GB GDDR7 PCI Express 5.0 x8 ATX Graphics Car | New | $565 | In stock | 5 h ago | Buy |
| eBayZOTAC ZTB50610H10A GeForce RTX 5060 Ti Twin Edge OC 8GB GDDR7 Graphics Card NEW | New | $570 | In stock | 5 h ago | Buy |
| eBayASUS Dual GeForce RTX 5060 Ti 8GB GDDR7 PCI Express 5.0 x8 ATX Graphics Card DUA | New | $574 | In stock | 5 h ago | Buy |
Used on eBay: median asking price $530, most between $500 and $580 (23 listings, 2026-11-03). Used price history
Price history
Lowest price shown each day over the last 90 days.
Not enough price history yet.
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 |
|---|---|---|---|---|---|---|---|
| gpt-oss 20B OpenAI | MXFP4 | fits | 13.3 GB | 82k128k with q8 cache | 52tok/sest. | 917 tok/s | chat, coding, agents, long documents |
| Gemma 4 12B | Q8_0 | fits | 13.9 GB | 73k122k with q8 cache | 21tok/sest. | 399 tok/s | chat, coding |
| Qwen 3.5 9B Alibaba Qwen | Q8_0 | fits | 11.2 GB | 128k212k with q8 cache | 26tok/sest. | 497 tok/s | chat, coding, long documents |
| Ministral 3 14B Mistral AI | Q4_K_M | fits | 14.0 GB | 37k67k with q8 cache | 20tok/sest. | 276 tok/s | chat, coding |
| Qwen3 14B Alibaba Qwen | Q4_K_M | fits | 14.7 GB | 32k40k with q8 cache | 19tok/sest. | 248 tok/s | chat |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q8_0 | fits | 13.9 GB | 38k69k with q8 cache | 21tok/sest. | 410 tok/s | chat, coding |
| Qwen3 8B Alibaba Qwen | Q8_0 | fits | 13.9 GB | 38k40k with q8 cache | 21tok/sest. | 410 tok/s | chat, coding |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 6.5 GB | 255k256k with q8 cache | 50tok/sest. | 930 tok/s | chat, coding, long documents |
| Granite 4.2 8B IBM | Q6_K | fits | 13.3 GB | 41k75k with q8 cache | 22tok/sest. | 377 tok/s | chat, coding |
| Ministral 3 8B Mistral AI | Q8_0 | fits | 13.9 GB | 38k69k with q8 cache | 20tok/sest. | 396 tok/s | chat, coding |
| Gemma 4 E4B | Q8_0 | fits | 9.8 GB | 128k | 30tok/sest. | 625 tok/s | chat, coding, long documents |
| LFM2.5 8B-A1B Liquid AI | Q8_0 | fits | 11.2 GB | 100k125k with q8 cache | 62tok/sest. | 2043 tok/s | chat, coding, long documents |
| Llama 3.1 8B Meta | Q6_K | fits | 11.4 GB | 57k104k with q8 cache | 26tok/sest. | 433 tok/s | chat, coding |
| Qwen2.5 0.5B Alibaba Qwen | Q8_0 | fits | 2.2 GB | 32k | 298tok/sest. | 4449 tok/s | chat, coding, long documents |
| Qwen3.5 0.8B Alibaba Qwen | Q8_0 | fits | 2.4 GB | 256k | 225tok/sest. | 4180 tok/s | chat, coding, agents, long documents |
| Qwen3.5 2B Alibaba Qwen | Q5_K_M | fits | 3.0 GB | 256k | 150tok/sest. | 1993 tok/s | chat, coding, agents, long documents |
| LFM3 1.7B Liquid AI | Q8_0 | fits | 3.4 GB | 256k | 123tok/sest. | 2480 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 1.5B DeepSeek | Q8_0 | fits | 3.9 GB | 128k | 98tok/sest. | 1674 tok/s | chat, coding, long documents |
| MiniCPM5 2B openbmb | Q8_0 | fits | 5.1 GB | 128k | 68tok/sest. | 1000 tok/s | chat, coding, agents, long documents |
| Spark X2.5 4B XHToken | mlx-4bit | fits | 5.3 GB | 263k441k with q8 cache | 65tok/sest. | 982 tok/s | chat, coding, agents, long documents |
| LFM2.5 2.6B Liquid AI | Q8_0 | fits | 5.8 GB | 128k | 57tok/sest. | 1132 tok/s | chat, coding, agents, long documents |
| LFM2.5 VL 3B Liquid AI | Q8_0 | fits | 5.8 GB | 32k | 57tok/sest. | 1038 tok/s | chat, coding, agents, long documents |
| Kimi VL A3B Thinking 2506 Moonshot AI | Q4_K_M | fits | 12.1 GB | 109k128k with q8 cache | 57tok/sest. | 1108 tok/s | chat, coding, long documents |
| Mellum2.1 12B A2.5B Thinking JetBrains | Q8_0 | fits | 13.8 GB | 83k125k with q8 cache | 53tok/sest. | 1475 tok/s | chat, coding, agents, long documents |
| Kimi VL A3B Moonshot AI | mlx-5bit | fits | 13.3 GB | 75k123k with q8 cache | 52tok/sest. | 933 tok/s | chat, coding, agents, long documents |
| FrogNano 4B 2609 Microsoft | Q8_0 | fits | 6.6 GB | 251k256k with q8 cache | 48tok/sest. | 930 tok/s | chat, coding, agents, long documents |
| granite vision 4.1 4b IBM | Q8_0 | fits | 7.2 GB | 122k128k with q8 cache | 44tok/sest. | 725 tok/s | chat, coding, long documents |
| granite 4.2 3b IBM | Q8_0 | fits | 7.4 GB | 119k128k with q8 cache | 42tok/sest. | 760 tok/s | chat, coding, agents, long documents |
| Ministral 3 3B Instruct 2512 Mistral AI | Q8_0 | fits | 7.9 GB | 95k172k with q8 cache | 39tok/sest. | 727 tok/s | chat, coding, agents |
| GLM 4 9B 0414 Z.ai | mlx-5bit | fits | 10.2 GB | 32k | 29tok/sest. | 361 tok/s | chat, coding |
| DeepSeek R1 Distill Qwen 7B DeepSeek | Q8_0 | fits | 10.6 GB | 101k128k with q8 cache | 28tok/sest. | 489 tok/s | chat, coding |
| GLM 4.6V Flash Z.ai | Q8_0 | fits | 11.9 GB | 97k128k with q8 cache | 25tok/sest. | 341 tok/s | chat, coding |
| DeepSeek R1 Distill Llama 8B DeepSeek | Q8_0 | fits | 13.2 GB | 43k79k with q8 cache | 22tok/sest. | 433 tok/s | chat, coding |
| GLM 4.1V 9B Thinking Z.ai | mlx-8bit | fits | 13.5 GB | 60k64k with q8 cache | 21tok/sest. | 341 tok/s | chat, coding |
| Ministral 3 14B Reasoning 2512 Mistral AI | Q4_K_M | fits | 14.0 GB | 37k67k with q8 cache | 20tok/sest. | 276 tok/s | chat, coding |
| Ministral 3 8B Reasoning 2512 Mistral AI | Q8_0 | fits | 13.9 GB | 38k69k with q8 cache | 20tok/sest. | 396 tok/s | chat, coding |
| Qwen 3.8 27B Alibaba Qwen | UD-Q4_K_M | offload | 18.8 GB | – | 8tok/sest. | 149 tok/s | – |
| Qwen 3.6 27B Alibaba Qwen | Q4_K_M | offload | 19.1 GB | – | 7tok/sest. | 147 tok/s | – |
| Gemma 4 31B | Q4_K_M | offload | 21.6 GB | – | 5tok/sest. | 122 tok/s | – |
| Mistral Small 4 119B Mistral AI | UD-Q2_K_XL | offload | 39.4 GB | – | 14tok/sest. | 275 tok/s | chat |
| Qwen 3.6 35B-A3B Alibaba Qwen | MXFP4 | offload | 22.2 GB | – | 27tok/sest. | 968 tok/s | chat, coding |
| Qwen 3.5 27B Alibaba Qwen | Q4_K_M | offload | 19.0 GB | – | 7tok/sest. | 148 tok/s | – |
| Gemma 4 26B-A4B | MXFP4 | offload | 17.5 GB | – | 29tok/sest. | 983 tok/s | chat, coding |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q4_K_M | offload | 22.5 GB | – | 26tok/sest. | 961 tok/s | chat, coding |
| GLM 4.7 Flash Z.ai | Q4_K_M | offload | 20.0 GB | – | 16tok/sest. | 534 tok/s | chat |
| Devstral Small 2 24B Mistral AI | Q4_K_M | offload | 19.6 GB | 2k3k with q8 cache | 7tok/sest. | 153 tok/s | – |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | MXFP4 | offload | 23.1 GB | – | 26tok/sest. | 1081 tok/s | chat, coding, long documents |
| Kimi Linear 48B-A3B Moonshot AI | Q4_K_M | offload | 29.6 GB | – | 25tok/sest. | 727 tok/s | chat, coding, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q4_K_M | offload | 21.6 GB | – | 14tok/sest. | 452 tok/s | chat |
| Qwen3 32B Alibaba Qwen | Q4_K_M | offload | 27.7 GB | – | 3tok/sest. | 76 tok/s | – |
| Gemma 3 27B | Q4_K_M | offload | 19.6 GB | – | 7tok/sest. | 154 tok/s | – |
| Mistral Small 3.2 24B Mistral AI | Q4_K_M | offload | 19.6 GB | 2k3k with q8 cache | 7tok/sest. | 153 tok/s | – |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q4_K_M | offload | 27.8 GB | – | 3tok/sest. | 87 tok/s | – |
| Phi-4 14B Microsoft | Q4_K_M | offload | 15.8 GB | 16k | 14tok/sest. | 239 tok/s | chat |
| LFM2.5 24B A2B Liquid AI | Q4_K_M | offload | 18.1 GB | – | 23tok/sest. | 1005 tok/s | chat, coding |
| DeepSeek R1 Distill Qwen 14B DeepSeek | Q4_K_M | offload | 15.7 GB | 27k50k with q8 cache | 14tok/sest. | 225 tok/s | chat |
| Muse Glimmer 30B meta-models | Q4_K_M | offload | 17.9 GB | – | 9tok/sest. | 147 tok/s | – |
| Devstral Small 2507 Mistral AI | Q4_K_M | offload | 19.6 GB | 2k3k with q8 cache | 7tok/sest. | 155 tok/s | – |
| Magistral Small 2506 Mistral AI | Q4_K_M | offload | 19.6 GB | 2k3k with q8 cache | 7tok/sest. | 155 tok/s | – |
| Magistral Small 2507 Mistral AI | Q4_K_M | offload | 19.6 GB | 2k3k with q8 cache | 7tok/sest. | 155 tok/s | – |
| Magistral Small 2509 Mistral AI | Q4_K_M | offload | 19.6 GB | 2k3k with q8 cache | 7tok/sest. | 153 tok/s | – |
| Qwen3.8 27B OBLITERATED OBLITERATUS | mlx-4bit | offload | 22.7 GB | – | 5tok/sest. | 134 tok/s | – |
| granite 4.2 30b IBM | Q4_K_M | offload | 26.1 GB | – | 4tok/sest. | 102 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 | – | – | – | – |
| Qwen 3.5 122B-A10B Alibaba Qwen | UD-Q2_K_XL | won't run | 41.1 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 | 47.3 GB | – | – | – | – |
| gpt-oss 120B OpenAI | Q4_K_M | won't run | 60.9 GB | – | – | – | – |
| GLM 4.5 Air Z.ai | Q2_K | won't run | 49.2 GB | – | – | – | – |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q4_K_M | won't run | 47.3 GB | – | – | – | – |
| Llama 3.3 70B Meta | Q4_K_M | won't run | 50.9 GB | – | – | – | – |
| DeepSeek R1 DeepSeek | Q4_K_M | won't run | 380.1 GB | – | – | – | – |
| DeepSeek R1 0528 DeepSeek | Q4_K_M | won't run | 380.6 GB | – | – | – | – |
| DeepSeek R1 Distill Llama 70B DeepSeek | Q4_K_M | won't run | 50.9 GB | – | – | – | – |
| DeepSeek R1 Zero DeepSeek | Q4_K_M | won't run | 380.1 GB | – | – | – | – |
| DeepSeek V3 DeepSeek | Q4_K_M | won't run | 380.1 GB | – | – | – | – |
| DeepSeek V3 0324 DeepSeek | Q4_K_M | won't run | 380.1 GB | – | – | – | – |
| DeepSeek V3.1 DeepSeek | Q4_K_M | won't run | 381.0 GB | – | – | – | – |
| DeepSeek V3.1 Terminus DeepSeek | Q4_K_M | won't run | 381.0 GB | – | – | – | – |
| DeepSeek V3.2 DeepSeek | Q4_K_M | won't run | 381.0 GB | – | – | – | – |
| DeepSeek V4 Flash 0731 DeepSeek | MXFP4 | won't run | 149.6 GB | – | – | – | – |
| DeepSeek V4 Flash Vision Exp DeepSeek | MXFP4 | won't run | 158.4 GB | – | – | – | – |
| Devstral 2 123B Instruct 2512 Mistral AI | Q4_K_M | won't run | 82.0 GB | – | – | – | – |
| GLM 4.5 Z.ai | Q4_K_M | won't run | 214.4 GB | – | – | – | – |
| GLM 4.5V Z.ai | Q4_K_M | won't run | 66.3 GB | – | – | – | – |
| GLM 4.6 Z.ai | Q4_K_M | won't run | 213.6 GB | – | – | – | – |
| GLM 4.6V Z.ai | Q4_K_M | won't run | 72.6 GB | – | – | – | – |
| GLM 4.7 Z.ai | Q4_K_M | won't run | 214.4 GB | – | – | – | – |
| GLM 5 Z.ai | MXFP4 | won't run | 386.4 GB | – | – | – | – |
| GLM 5.1 Z.ai | MXFP4 | won't run | 424.0 GB | – | – | – | – |
| GLM 5.2 Z.ai | UD-Q4_K_M | won't run | 437.9 GB | – | – | – | – |
| GLM 5.3 Z.ai | Q8_0 | won't run | 750.4 GB | – | – | – | – |
| Kimi Dev 72B Moonshot AI | Q6_K | won't run | 71.2 GB | – | – | – | – |
| Kimi K2 Moonshot AI | Q4_K_M | won't run | 581.6 GB | – | – | – | – |
| Kimi K2 Instruct 0905 Moonshot AI | Q4_K_M | won't run | 582.0 GB | – | – | – | – |
| Kimi K2 Thinking Moonshot AI | Q4_K_M | won't run | 582.0 GB | – | – | – | – |
| Kimi K2.5 Moonshot AI | Q4_K_M | won't run | 582.0 GB | – | – | – | – |
| MiniMax M2 MiniMax | Q4_K_M | won't run | 137.9 GB | – | – | – | – |
| MiniMax M2.1 MiniMax | Q4_K_M | won't run | 137.9 GB | – | – | – | – |
| MiniMax M2.5 MiniMax | MXFP4 | won't run | 124.3 GB | – | – | – | – |
| MiniMax M3 MiniMax | MXFP4 | won't run | 244.7 GB | – | – | – | – |
| Mistral Medium 3.5 128B Mistral AI | Q4_K_M | won't run | 82.0 GB | – | – | – | – |
Specifications
From the manufacturer's published specifications; sources are linked where we have them.
- GPU
- GeForce RTX 5060 Ti 8GB
- Memory
- 8 GB GDDR7
- Memory bus
- 128-bit
- Memory bandwidth
- 448 GB/s
- FP16 compute
- 23.704 TFLOPS
- Software
- CUDA
- Board power
- 180 W
- PCIe generation
- Gen 5
- PCIe lanes
- x8
Compare with
Questions
- How much memory does the NVIDIA GeForce RTX 5060 Ti 8GB have for AI models?
- The NVIDIA GeForce RTX 5060 Ti 8GB 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 Ti 8GB can run locally?
- gpt-oss 20B (MXFP4) fits fully in its memory at 32k context and generates at about 52 tok/s, an estimate from its memory bandwidth. 36 of the 129 models we track fit at that context.
- Can the NVIDIA GeForce RTX 5060 Ti 8GB 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 5060 Ti 8GB and system RAM can hold.
- How much does the NVIDIA GeForce RTX 5060 Ti 8GB cost in the US?
- The best new price for the NVIDIA GeForce RTX 5060 Ti 8GB in the US is $510 at eBay; used, it starts at $450 (asking price).
Speeds on this page are for 32k context. See the best hardware for local AI at every budget.