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 64k context it runs 27 of the 129 open models we track fully in memory; the most capable is gpt-oss 20B at MXFP4, at about 41 tok/s (estimated). The best new price for the NVIDIA GeForce RTX 5060 Ti 8GB in the UK is £505 at eBay; used, it starts at £425 (asking price).
Updated . Speeds are estimates; how they are worked out.
Prices
Every retailer we track in the UK, cheapest first. Buy links may earn us a commission.
| Retailer | Condition | Price | Stock | Checked | Buy |
|---|---|---|---|---|---|
| eBayGigabyte RTX 5060 Ti EAGLE OC 8GB GV-N506TEAGLE OC-8GD | used, asking price | £425 | In stock | 40 min ago | Buy |
| eBayMSI RTX 5060 Ti Gaming Trio OC 8GB GDDR7 Blackwell GPU | used, asking price | £429 | In stock | 40 min ago | Buy |
| eBayPalit NVIDIA GeForce RTX 5060 Ti White OC 8GB GDDR7 Ray-Tracing Graphics Card | New | £505 | In stock | 40 min ago | Buy |
| eBayGigabyte GeForce RTX 5060 Ti AERO OC 8G Graphics Card | used, asking price | £499+ £9 delivery | In stock | 40 min ago | Buy |
| eBayGIGABYTE GeForce RTX 5060 Ti EAGLE OC 8GB RAM RTX 5060 Ti GPU | New | £510 | In stock | 40 min ago | Buy |
| eBayGIGABYTE GeForce RTX 5060 Ti EAGLE OC 8GB RAM RTX 5060 Ti GPU | New | £510 | In stock | 40 min ago | Buy |
| eBayASUS Dual GeForce RTX 5060 Ti OC 8GB Graphics Card | New | £520 | In stock | 40 min ago | Buy |
| eBayPalit: Geforce RTX 5060 TI Duel 8GB | used, asking price | £537+ £7 delivery | In stock | 40 min ago | Buy |
| eBayGIGABYTE GeForce RTX 5060 Ti EAGLE OC ICE 8GB GDDR7 Graphics Card | New | £551 | In stock | 40 min ago | Buy |
| eBayGIGABYTE GeForce RTX 5060 Ti Gaming OC 8GB GDDR7 PCIe Ray Tracing | New | £560 | In stock | 40 min ago | Buy |
| eBayINNO3D NVIDIA GeForce RTX 5060 Ti Twin X2 8GB GDDR7 Ray-Tracing Graphics Card | New | £563 | In stock | 40 min ago | Buy |
| eBayPalit GeForce RTX 5060 Ti Dual OC NVIDIA 8 GB GDDR7 | New | £576 | In stock | 40 min ago | Buy |
| eBayMSI GeForce RTX 5060 Ti GAMING TRIO OC 8GB GDDR7 | New | £580 | In stock | 40 min ago | Buy |
Price history
Lowest price shown each day over the last 90 days.
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 @64k | Prefill | Good for |
|---|---|---|---|---|---|---|---|
| gpt-oss 20B OpenAI | MXFP4 | fits | 14.3 GB | 82k128k with q8 cache | 41tok/sest. | 718 tok/s | chat, coding, agents, long documents |
| Gemma 4 12B | Q8_0 | fits | 14.6 GB | 73k122k with q8 cache | 20tok/sest. | 369 tok/s | chat, coding |
| Qwen 3.5 9B Alibaba Qwen | Q8_0 | fits | 12.4 GB | 128k212k with q8 cache | 24tok/sest. | 452 tok/s | chat, coding, long documents |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 7.7 GB | 255k256k with q8 cache | 42tok/sest. | 784 tok/s | chat, coding, long documents |
| Gemma 4 E4B | Q8_0 | fits | 10.9 GB | 128k | 28tok/sest. | 592 tok/s | chat, coding, long documents |
| LFM2.5 8B-A1B Liquid AI | Q8_0 | fits | 12.9 GB | 100k125k with q8 cache | 39tok/sest. | 1264 tok/s | chat, coding, long documents |
| Llama 3.1 8B Meta | Q4_K_M | fits | 14.1 GB | 69k126k with q8 cache | 21tok/sest. | 321 tok/s | chat, coding |
| Qwen2.5 0.5B Alibaba Qwen | Q8_0 | fits | 2.7 GB | 32k | 208tok/sest. | 2802 tok/s | chat, coding, long documents |
| Qwen3.5 0.8B Alibaba Qwen | Q8_0 | fits | 3.0 GB | 256k | 170tok/sest. | 3177 tok/s | chat, coding, agents, long documents |
| Qwen3.5 2B Alibaba Qwen | Q5_K_M | fits | 3.6 GB | 256k | 123tok/sest. | 1732 tok/s | chat, coding, agents, long documents |
| LFM3 1.7B Liquid AI | Q8_0 | fits | 4.0 GB | 256k | 104tok/sest. | 2089 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 1.5B DeepSeek | Q8_0 | fits | 5.0 GB | 128k | 74tok/sest. | 1161 tok/s | chat, coding, long documents |
| MiniCPM5 2B openbmb | Q8_0 | fits | 6.6 GB | 128k | 51tok/sest. | 654 tok/s | chat, coding, agents, long documents |
| Spark X2.5 4B XHToken | mlx-4bit | fits | 6.6 GB | 263k441k with q8 cache | 50tok/sest. | 803 tok/s | chat, coding, agents, long documents |
| Mellum2.1 12B A2.5B Thinking JetBrains | Q8_0 | fits | 14.4 GB | 83k125k with q8 cache | 46tok/sest. | 1171 tok/s | chat, coding, agents, long documents |
| Kimi VL A3B Thinking 2506 Moonshot AI | Q4_K_M | fits | 13.2 GB | 109k128k with q8 cache | 42tok/sest. | 805 tok/s | chat, coding, long documents |
| FrogNano 4B 2609 Microsoft | Q8_0 | fits | 7.8 GB | 251k256k with q8 cache | 41tok/sest. | 784 tok/s | chat, coding, agents, long documents |
| LFM2.5 2.6B Liquid AI | Q8_0 | fits | 7.9 GB | 128k | 40tok/sest. | 793 tok/s | chat, coding, agents, long documents |
| LFM2.5 VL 3B Liquid AI | Q8_0 | fits | 7.9 GB | 32k | 40tok/sest. | 746 tok/s | chat, coding, agents, long documents |
| Kimi VL A3B Moonshot AI | mlx-5bit | fits | 14.4 GB | 75k123k with q8 cache | 40tok/sest. | 632 tok/s | chat, coding, agents, long documents |
| granite vision 4.1 4b IBM | Q8_0 | fits | 9.8 GB | 122k128k with q8 cache | 31tok/sest. | 498 tok/s | chat, coding, long documents |
| granite 4.2 3b IBM | Q8_0 | fits | 10.1 GB | 119k128k with q8 cache | 30tok/sest. | 514 tok/s | chat, coding, agents, long documents |
| Ministral 3 3B Instruct 2512 Mistral AI | Q8_0 | fits | 11.4 GB | 95k172k with q8 cache | 26tok/sest. | 493 tok/s | chat, coding, agents |
| GLM 4 9B 0414 Z.ai | mlx-5bit | fits | 11.7 GB | 32k | 25tok/sest. | 265 tok/s | chat, coding |
| DeepSeek R1 Distill Qwen 7B DeepSeek | Q8_0 | fits | 12.5 GB | 101k128k with q8 cache | 23tok/sest. | 376 tok/s | chat, coding |
| GLM 4.6V Flash Z.ai | Q8_0 | fits | 13.3 GB | 97k128k with q8 cache | 22tok/sest. | 254 tok/s | chat, coding |
| DeepSeek R1 Distill Llama 8B DeepSeek | Q4_K_M | fits | 14.1 GB | 69k126k with q8 cache | 21tok/sest. | 321 tok/s | chat, coding |
| Qwen 3.8 27B Alibaba Qwen | UD-Q4_K_M | offload | 20.9 GB | – | 6tok/sest. | 126 tok/s | – |
| Qwen 3.6 27B Alibaba Qwen | Q4_K_M | offload | 21.3 GB | – | 6tok/sest. | 125 tok/s | – |
| Gemma 4 31B | Q4_K_M | offload | 24.3 GB | – | 4tok/sest. | 107 tok/s | – |
| Mistral Small 4 119B Mistral AI | UD-Q2_K_XL | offload | 40.3 GB | – | 12tok/sest. | 193 tok/s | chat |
| Qwen 3.6 35B-A3B Alibaba Qwen | MXFP4 | offload | 23.0 GB | – | 20tok/sest. | 724 tok/s | chat, coding |
| Qwen 3.5 27B Alibaba Qwen | Q4_K_M | offload | 21.2 GB | – | 6tok/sest. | 126 tok/s | – |
| Gemma 4 26B-A4B | MXFP4 | offload | 18.3 GB | – | 22tok/sest. | 840 tok/s | chat, coding |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q4_K_M | offload | 23.3 GB | – | 20tok/sest. | 719 tok/s | chat, coding |
| GLM 4.7 Flash Z.ai | Q4_K_M | offload | 21.8 GB | – | 10tok/sest. | 369 tok/s | chat |
| Devstral Small 2 24B Mistral AI | Q4_K_M | offload | 24.8 GB | 2k3k with q8 cache | 4tok/sest. | 114 tok/s | – |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | MXFP4 | offload | 23.5 GB | – | 24tok/sest. | 882 tok/s | chat, coding, long documents |
| Kimi Linear 48B-A3B Moonshot AI | Q4_K_M | offload | 30.0 GB | – | 22tok/sest. | 513 tok/s | chat, coding, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q4_K_M | offload | 24.8 GB | – | 7tok/sest. | 250 tok/s | chat |
| Qwen3 32B Alibaba Qwen | Q4_K_M | offload | 35.9 GB | – | 2tok/sest. | 50 tok/s | – |
| Gemma 3 27B | Q4_K_M | offload | 22.3 GB | – | 5tok/sest. | 137 tok/s | – |
| Mistral Small 3.2 24B Mistral AI | Q4_K_M | offload | 24.8 GB | 2k3k with q8 cache | 4tok/sest. | 114 tok/s | – |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q4_K_M | offload | 36.0 GB | – | 2tok/sest. | 62 tok/s | – |
| Ministral 3 14B Mistral AI | Q4_K_M | offload | 19.1 GB | 37k67k with q8 cache | 7tok/sest. | 184 tok/s | chat, coding |
| Qwen3 14B Alibaba Qwen | Q4_K_M | offload | 19.9 GB | 32k40k with q8 cache | 7tok/sest. | 158 tok/s | chat |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q4_K_M | offload | 15.2 GB | 61k111k with q8 cache | 17tok/sest. | 294 tok/s | chat, coding |
| Qwen3 8B Alibaba Qwen | Q4_K_M | offload | 15.2 GB | 40k | 17tok/sest. | 294 tok/s | chat, coding |
| Phi-4 14B Microsoft | Q4_K_M | offload | 22.3 GB | 16k | 5tok/sest. | 149 tok/s | chat |
| Ministral 3 8B Mistral AI | Q4_K_M | offload | 14.8 GB | 63k115k with q8 cache | 19tok/sest. | 295 tok/s | chat, coding |
| Granite 4.2 8B IBM | Q4_K_M | offload | 16.6 GB | 52k96k with q8 cache | 11tok/sest. | 253 tok/s | chat, coding |
| Ministral 3 8B Reasoning 2512 Mistral AI | Q4_K_M | offload | 14.8 GB | 63k115k with q8 cache | 19tok/sest. | 295 tok/s | chat, coding |
| GLM 4.1V 9B Thinking Z.ai | mlx-8bit | offload | 14.9 GB | 60k64k with q8 cache | 18tok/sest. | 252 tok/s | chat, coding |
| LFM2.5 24B A2B Liquid AI | Q4_K_M | offload | 20.8 GB | – | 11tok/sest. | 589 tok/s | chat, coding |
| Muse Glimmer 30B meta-models | Q4_K_M | offload | 18.5 GB | – | 8tok/sest. | 137 tok/s | – |
| Ministral 3 14B Reasoning 2512 Mistral AI | Q4_K_M | offload | 19.1 GB | 37k67k with q8 cache | 7tok/sest. | 184 tok/s | chat, coding |
| DeepSeek R1 Distill Qwen 14B DeepSeek | Q4_K_M | offload | 21.8 GB | 27k50k with q8 cache | 5tok/sest. | 137 tok/s | chat |
| Devstral Small 2507 Mistral AI | Q4_K_M | offload | 24.8 GB | 2k3k with q8 cache | 4tok/sest. | 115 tok/s | – |
| Magistral Small 2506 Mistral AI | Q4_K_M | offload | 24.8 GB | 2k3k with q8 cache | 4tok/sest. | 115 tok/s | – |
| Magistral Small 2507 Mistral AI | Q4_K_M | offload | 24.8 GB | 2k3k with q8 cache | 4tok/sest. | 115 tok/s | – |
| Magistral Small 2509 Mistral AI | Q4_K_M | offload | 24.8 GB | 2k3k with q8 cache | 4tok/sest. | 114 tok/s | – |
| Qwen3.8 27B OBLITERATED OBLITERATUS | mlx-4bit | offload | 24.9 GB | – | 4tok/sest. | 116 tok/s | – |
| granite 4.2 30b IBM | Q4_K_M | offload | 34.3 GB | – | 2tok/sest. | 74 tok/s | – |
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | won't run | 97.0 GB | – | – | – | – |
| GLM 5.3 Flash Z.ai | UD-Q2_K_XL | won't run | 103.5 GB | – | – | – | – |
| Qwen 3.8 Flash Next Alibaba Qwen | UD-Q2_K_XL | won't run | 76.5 GB | – | – | – | – |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | won't run | 87.1 GB | – | – | – | – |
| Qwen 3.5 122B-A10B Alibaba Qwen | UD-Q2_K_XL | won't run | 42.1 GB | – | – | – | – |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q2_K_XL | won't run | 53.0 GB | – | – | – | – |
| Qwen3 Coder Next Alibaba Qwen | Q4_K_M | won't run | 48.2 GB | – | – | – | – |
| gpt-oss 120B OpenAI | Q4_K_M | won't run | 62.2 GB | – | – | – | – |
| GLM 4.5 Air Z.ai | Q2_K | won't run | 55.2 GB | – | – | – | – |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q4_K_M | won't run | 48.2 GB | – | – | – | – |
| Llama 3.3 70B Meta | Q4_K_M | won't run | 61.1 GB | – | – | – | – |
| DeepSeek R1 DeepSeek | Q4_K_M | won't run | 382.4 GB | – | – | – | – |
| DeepSeek R1 0528 DeepSeek | Q4_K_M | won't run | 382.9 GB | – | – | – | – |
| DeepSeek R1 Distill Llama 70B DeepSeek | Q4_K_M | won't run | 61.1 GB | – | – | – | – |
| DeepSeek R1 Zero DeepSeek | Q4_K_M | won't run | 382.4 GB | – | – | – | – |
| DeepSeek V3 DeepSeek | Q4_K_M | won't run | 382.4 GB | – | – | – | – |
| DeepSeek V3 0324 DeepSeek | Q4_K_M | won't run | 382.4 GB | – | – | – | – |
| DeepSeek V3.1 DeepSeek | Q4_K_M | won't run | 383.3 GB | – | – | – | – |
| DeepSeek V3.1 Terminus DeepSeek | Q4_K_M | won't run | 383.3 GB | – | – | – | – |
| DeepSeek V3.2 DeepSeek | Q4_K_M | won't run | 383.3 GB | – | – | – | – |
| DeepSeek V4 Flash 0731 DeepSeek | MXFP4 | won't run | 152.5 GB | – | – | – | – |
| DeepSeek V4 Flash Vision Exp DeepSeek | MXFP4 | won't run | 161.3 GB | – | – | – | – |
| Devstral 2 123B Instruct 2512 Mistral AI | Q4_K_M | won't run | 93.2 GB | – | – | – | – |
| GLM 4.5 Z.ai | Q4_K_M | won't run | 226.1 GB | – | – | – | – |
| GLM 4.5V Z.ai | Q4_K_M | won't run | 72.2 GB | – | – | – | – |
| GLM 4.6 Z.ai | Q4_K_M | won't run | 225.3 GB | – | – | – | – |
| GLM 4.6V Z.ai | Q4_K_M | won't run | 78.6 GB | – | – | – | – |
| GLM 4.7 Z.ai | Q4_K_M | won't run | 226.1 GB | – | – | – | – |
| GLM 5 Z.ai | MXFP4 | won't run | 389.3 GB | – | – | – | – |
| GLM 5.1 Z.ai | MXFP4 | won't run | 426.9 GB | – | – | – | – |
| GLM 5.2 Z.ai | UD-Q4_K_M | won't run | 440.8 GB | – | – | – | – |
| GLM 5.3 Z.ai | Q8_0 | won't run | 753.3 GB | – | – | – | – |
| Kimi Dev 72B Moonshot AI | Q6_K | won't run | 81.4 GB | – | – | – | – |
| Kimi K2 Moonshot AI | Q4_K_M | won't run | 583.9 GB | – | – | – | – |
| Kimi K2 Instruct 0905 Moonshot AI | Q4_K_M | won't run | 584.3 GB | – | – | – | – |
| Kimi K2 Thinking Moonshot AI | Q4_K_M | won't run | 584.3 GB | – | – | – | – |
| Kimi K2.5 Moonshot AI | Q4_K_M | won't run | 584.3 GB | – | – | – | – |
| MiniMax M2 MiniMax | Q4_K_M | won't run | 145.8 GB | – | – | – | – |
| MiniMax M2.1 MiniMax | Q4_K_M | won't run | 145.8 GB | – | – | – | – |
| MiniMax M2.5 MiniMax | MXFP4 | won't run | 132.2 GB | – | – | – | – |
| MiniMax M3 MiniMax | MXFP4 | won't run | 248.7 GB | – | – | – | – |
| Mistral Medium 3.5 128B Mistral AI | Q4_K_M | won't run | 93.2 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 64k context and generates at about 41 tok/s, an estimate from its memory bandwidth. 27 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 97 GB at 64k 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 UK?
- The best new price for the NVIDIA GeForce RTX 5060 Ti 8GB in the UK is £505 at eBay; used, it starts at £425 (asking price).
Speeds on this page are for 64k context. See the best hardware for local AI at every budget.