NVIDIA GeForce RTX 4060 Ti 8GB
8 GB · 288 GB/s · 160 W
In short
The NVIDIA GeForce RTX 4060 Ti 8GB has 8 GB of GDDR6 memory with 288 GB/s of bandwidth, which sets how fast it generates text. At 8k context it runs 26 of the 129 open models we track fully in memory; the most capable is Qwen 3.5 9B at Q5_K_M, at about 26 tok/s (estimated). The best new price for the NVIDIA GeForce RTX 4060 Ti 8GB in the US is $440 at eBay; used, it starts at $430 (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 |
|---|---|---|---|---|---|
| eBayMSI GeForce RTX 4060 Ti Ventus 3X 8GB GDRR6 OC 2580MHz Gaming Graphics Card | used, asking price | $430 | In stock | 5 h ago | Buy |
| eBayMSI GeForce RTX 4060 Ti VENTUS 2X BLACK 8G OC PCIe4 Video Graphics Card WARRANTY | refurbished | $439 | In stock | 5 h ago | Buy |
| eBayASUS Dual GeForce RTX 4060 Ti EVO OC 8GB GDDR6 DLSS 3 | New | $440 | In stock | 5 h ago | Buy |
| eBayUsed GeForce RTX 4060 Ti 8GB on eBay | used, asking price | $450 | In stock | 5 h ago | Buy |
| eBayPNY RTX 4060 Ti 8GB XLR8 Gaming VERTO EPIC-X RGB Triple Fan Graphics Card | refurbished | $450 | In stock | 5 h ago | Buy |
| eBayASUS Dual OC GeForce RTX 4060 Ti 8GB RAM | refurbished | $510 | In stock | 5 h ago | Buy |
| eBayMSI GeForce RTX 4060 Ti 8GB Gaming X GPU | refurbished | $550 | In stock | 5 h ago | Buy |
| eBayZotac GeForce RTX 4060 Ti 8GB Twin Edge OC D40610H | refurbished | $550 | In stock | 5 h ago | Buy |
| eBayAsus GeForce RTX 4060 Ti 8GB Dual OC GPU | refurbished | $550 | In stock | 5 h ago | Buy |
| eBayNew Gigabyte GeForce RTX 4060 Ti WINDFORCE OC 8GB GDDR6 Graphics Card | New | $586 | In stock | 5 h ago | Buy |
| eBayASUS TUF GeForce RTX 4060 Ti V2 OC Edition 8GB GDDR6 Graphics Card... | New | $610+ $6 delivery | In stock | 5 h ago | Buy |
| eBayMSI NVIDIA GeForce RTX 4060 Ti VENTUS 3X OC 8GB GDDR6 Triple Fan PCIe 4.0 Sealed | New | $700+ $20 delivery | In stock | 5 h ago | Buy |
| eBayGIGABYTE RTX 4060 Ti 8GB GDDR6 PCIe 4.0 GV-N406TWF2OCV2-8GD Unused | New | $1,100 | In stock | 5 h ago | Buy |
| eBayGigabyte GeForce RTX 4060 Ti WINDFORCE OC 8GB Graphics Card | New | $1,206 | In stock | 5 h ago | Buy |
Used on eBay: median asking price $450, most between $420 and $500 (21 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 it runs
Every model in the catalogue, with the best quant for this hardware. Estimates, not measurements.
| Model | Quant | Fits | Memory | Max context | Decode @8k | Prefill | Good for |
|---|---|---|---|---|---|---|---|
| Qwen 3.5 9B Alibaba Qwen | Q5_K_M | fits | 7.2 GB | 14k23k with q8 cache | 26tok/sest. | 500 tok/s | chat |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q5_K_M | fits | 7.3 GB | 8k15k with q8 cache | 25tok/sest. | 528 tok/s | chat |
| Qwen3 8B Alibaba Qwen | Q5_K_M | fits | 7.3 GB | 8k15k with q8 cache | 25tok/sest. | 528 tok/s | chat |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 5.2 GB | 66k110k with q8 cache | 37tok/sest. | 1007 tok/s | chat, coding |
| Ministral 3 8B Mistral AI | Q4_K_M | fits | 6.7 GB | 13k24k with q8 cache | 28tok/sest. | 494 tok/s | chat |
| Granite 4.2 8B IBM | Q4_K_M | fits | 7.2 GB | 9k17k with q8 cache | 26tok/sest. | 490 tok/s | chat |
| Gemma 4 E4B | Q5_K_M | fits | 6.1 GB | 46k77k with q8 cache | 31tok/sest. | 606 tok/s | chat, coding |
| LFM2.5 8B-A1B Liquid AI | UD-Q5_K_M | fits | 7.0 GB | 14k25k with q8 cache | 93tok/sest. | 3540 tok/s | chat, coding |
| Llama 3.1 8B Meta | Q5_K_M | fits | 7.1 GB | 10k18k with q8 cache | 26tok/sest. | 545 tok/s | chat |
| Qwen2.5 0.5B Alibaba Qwen | Q8_0 | fits | 1.3 GB | 32k | 283tok/sest. | 7408 tok/s | chat, coding, long documents |
| Qwen3.5 0.8B Alibaba Qwen | Q8_0 | fits | 1.6 GB | 256k | 192tok/sest. | 5097 tok/s | chat, coding, agents, long documents |
| Qwen3.5 2B Alibaba Qwen | Q5_K_M | fits | 2.2 GB | 256k | 115tok/sest. | 2091 tok/s | chat, coding, agents, long documents |
| LFM3 1.7B Liquid AI | Q8_0 | fits | 2.6 GB | 256k | 91tok/sest. | 2686 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 1.5B DeepSeek | Q8_0 | fits | 2.7 GB | 128k | 84tok/sest. | 2332 tok/s | chat, coding, long documents |
| MiniCPM5 2B openbmb | Q8_0 | fits | 3.6 GB | 89k128k with q8 cache | 59tok/sest. | 1541 tok/s | chat, coding, agents |
| LFM2.5 2.6B Liquid AI | Q8_0 | fits | 3.9 GB | 62k108k with q8 cache | 53tok/sest. | 1551 tok/s | chat, coding, agents |
| LFM2.5 VL 3B Liquid AI | Q8_0 | fits | 3.9 GB | 32k | 53tok/sest. | 1369 tok/s | chat, coding, agents |
| Spark X2.5 4B XHToken | mlx-4bit | fits | 3.9 GB | 93k156k with q8 cache | 53tok/sest. | 1097 tok/s | chat, coding, agents, long documents |
| granite vision 4.1 4b IBM | Q8_0 | fits | 4.7 GB | 39k70k with q8 cache | 42tok/sest. | 1027 tok/s | chat, coding |
| Ministral 3 3B Instruct 2512 Mistral AI | Q8_0 | fits | 5.0 GB | 30k55k with q8 cache | 40tok/sest. | 1052 tok/s | chat, coding |
| granite 4.2 3b IBM | Q8_0 | fits | 5.0 GB | 36k64k with q8 cache | 39tok/sest. | 1104 tok/s | chat, coding |
| FrogNano 4B 2609 Microsoft | Q8_0 | fits | 5.3 GB | 63k104k with q8 cache | 36tok/sest. | 1007 tok/s | chat, coding, agents |
| Ministral 3 8B Reasoning 2512 Mistral AI | Q4_K_M | fits | 6.7 GB | 13k24k with q8 cache | 28tok/sest. | 494 tok/s | chat |
| GLM 4.6V Flash Z.ai | Q4_K_M | fits | 6.8 GB | 21k35k with q8 cache | 28tok/sest. | 427 tok/s | chat, coding |
| DeepSeek R1 Distill Qwen 7B DeepSeek | Q6_K | fits | 7.0 GB | 14k25k with q8 cache | 27tok/sest. | 588 tok/s | chat |
| DeepSeek R1 Distill Llama 8B DeepSeek | Q5_K_M | fits | 7.1 GB | 10k18k with q8 cache | 26tok/sest. | 545 tok/s | chat |
| Qwen 3.8 27B Alibaba Qwen | UD-Q4_K_M | offload | 16.7 GB | – | 4tok/sest. | 113 tok/s | – |
| Qwen 3.6 27B Alibaba Qwen | Q4_K_M | offload | 17.0 GB | – | 4tok/sest. | 112 tok/s | – |
| Gemma 4 31B | Q4_K_M | offload | 19.2 GB | – | 4tok/sest. | 93 tok/s | – |
| Qwen 3.6 35B-A3B Alibaba Qwen | MXFP4 | offload | 21.2 GB | – | 21tok/sest. | 886 tok/s | chat |
| Qwen 3.5 27B Alibaba Qwen | Q4_K_M | offload | 17.0 GB | – | 4tok/sest. | 112 tok/s | – |
| Gemma 4 26B-A4B | MXFP4 | offload | 16.5 GB | – | 16tok/sest. | 741 tok/s | chat |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q4_K_M | offload | 21.5 GB | – | 20tok/sest. | 882 tok/s | chat |
| GLM 4.7 Flash Z.ai | Q4_K_M | offload | 18.2 GB | – | 13tok/sest. | 524 tok/s | – |
| Devstral Small 2 24B Mistral AI | Q4_K_M | offload | 15.3 GB | – | 5tok/sest. | 132 tok/s | – |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | MXFP4 | offload | 22.5 GB | – | 18tok/sest. | 906 tok/s | chat |
| gpt-oss 20B OpenAI | Q4_K_M | offload | 11.8 GB | – | 22tok/sest. | 821 tok/s | chat |
| Kimi Linear 48B-A3B Moonshot AI | Q4_K_M | offload | 28.8 GB | – | 20tok/sest. | 767 tok/s | chat |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q4_K_M | offload | 18.8 GB | – | 17tok/sest. | 669 tok/s | chat |
| Qwen3 32B Alibaba Qwen | Q4_K_M | offload | 21.2 GB | – | 3tok/sest. | 80 tok/s | – |
| Gemma 4 12B | Q4_K_M | offload | 7.8 GB | – | 21tok/sest. | 381 tok/s | chat |
| Mistral Small 3.2 24B Mistral AI | Q4_K_M | offload | 15.3 GB | – | 5tok/sest. | 132 tok/s | – |
| Gemma 3 27B | Q4_K_M | offload | 17.2 GB | – | 4tok/sest. | 113 tok/s | – |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q4_K_M | offload | 21.2 GB | – | 3tok/sest. | 83 tok/s | – |
| Ministral 3 14B Mistral AI | Q4_K_M | offload | 9.7 GB | – | 12tok/sest. | 275 tok/s | – |
| Qwen3 14B Alibaba Qwen | Q4_K_M | offload | 10.4 GB | – | 10tok/sest. | 246 tok/s | – |
| Phi-4 14B Microsoft | Q4_K_M | offload | 10.6 GB | – | 10tok/sest. | 245 tok/s | – |
| Mellum2.1 12B A2.5B Thinking JetBrains | Q4_K_M | offload | 9.1 GB | – | 37tok/sest. | 1496 tok/s | chat, coding |
| Kimi VL A3B Thinking 2506 Moonshot AI | Q4_K_M | offload | 10.8 GB | – | 28tok/sest. | 1146 tok/s | chat |
| LFM2.5 24B A2B Liquid AI | Q4_K_M | offload | 15.7 GB | – | 24tok/sest. | 1241 tok/s | chat |
| Kimi VL A3B Moonshot AI | mlx-5bit | offload | 12.0 GB | – | 23tok/sest. | 1018 tok/s | chat |
| GLM 4 9B 0414 Z.ai | mlx-4bit | offload | 7.6 GB | 2k4k with q8 cache | 22tok/sest. | 452 tok/s | chat |
| Ministral 3 14B Reasoning 2512 Mistral AI | Q4_K_M | offload | 9.7 GB | – | 12tok/sest. | 275 tok/s | – |
| DeepSeek R1 Distill Qwen 14B DeepSeek | Q4_K_M | offload | 10.6 GB | – | 10tok/sest. | 238 tok/s | – |
| GLM 4.1V 9B Thinking Z.ai | mlx-8bit | offload | 12.0 GB | – | 8tok/sest. | 322 tok/s | – |
| Devstral Small 2507 Mistral AI | Q4_K_M | offload | 15.3 GB | – | 5tok/sest. | 134 tok/s | – |
| Magistral Small 2506 Mistral AI | Q4_K_M | offload | 15.3 GB | – | 5tok/sest. | 134 tok/s | – |
| Magistral Small 2507 Mistral AI | Q4_K_M | offload | 15.3 GB | – | 5tok/sest. | 134 tok/s | – |
| Magistral Small 2509 Mistral AI | Q4_K_M | offload | 15.3 GB | – | 5tok/sest. | 132 tok/s | – |
| Muse Glimmer 30B meta-models | Q4_K_M | offload | 17.0 GB | – | 4tok/sest. | 104 tok/s | – |
| granite 4.2 30b IBM | Q4_K_M | offload | 19.5 GB | – | 4tok/sest. | 97 tok/s | – |
| Qwen3.8 27B OBLITERATED OBLITERATUS | mlx-4bit | offload | 20.6 GB | – | 3tok/sest. | 104 tok/s | – |
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | won't run | 91.6 GB | – | – | – | – |
| GLM 5.3 Flash Z.ai | UD-Q2_K_XL | won't run | 102.2 GB | – | – | – | – |
| Qwen 3.8 Flash Next Alibaba Qwen | UD-Q2_K_XL | won't run | 74.5 GB | – | – | – | – |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | won't run | 72.8 GB | – | – | – | – |
| Qwen 3.5 122B-A10B Alibaba Qwen | UD-Q2_K_XL | won't run | 40.0 GB | – | – | – | – |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q2_K_XL | won't run | 51.9 GB | – | – | – | – |
| Qwen3 Coder Next Alibaba Qwen | Q4_K_M | won't run | 46.2 GB | – | – | – | – |
| gpt-oss 120B OpenAI | Q4_K_M | won't run | 59.5 GB | – | – | – | – |
| Mistral Small 4 119B Mistral AI | UD-Q2_K_XL | won't run | 38.4 GB | – | – | – | – |
| GLM 4.5 Air Z.ai | Q2_K | won't run | 44.4 GB | – | – | – | – |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q4_K_M | won't run | 46.2 GB | – | – | – | – |
| Llama 3.3 70B Meta | Q4_K_M | won't run | 42.8 GB | – | – | – | – |
| DeepSeek R1 DeepSeek | Q4_K_M | won't run | 377.9 GB | – | – | – | – |
| DeepSeek R1 0528 DeepSeek | Q4_K_M | won't run | 378.4 GB | – | – | – | – |
| DeepSeek R1 Distill Llama 70B DeepSeek | Q4_K_M | won't run | 42.8 GB | – | – | – | – |
| DeepSeek R1 Zero DeepSeek | Q4_K_M | won't run | 377.9 GB | – | – | – | – |
| DeepSeek V3 DeepSeek | Q4_K_M | won't run | 377.9 GB | – | – | – | – |
| DeepSeek V3 0324 DeepSeek | Q4_K_M | won't run | 377.9 GB | – | – | – | – |
| DeepSeek V3.1 DeepSeek | Q4_K_M | won't run | 378.8 GB | – | – | – | – |
| DeepSeek V3.1 Terminus DeepSeek | Q4_K_M | won't run | 378.8 GB | – | – | – | – |
| DeepSeek V3.2 DeepSeek | Q4_K_M | won't run | 378.8 GB | – | – | – | – |
| DeepSeek V4 Flash 0731 DeepSeek | MXFP4 | won't run | 147.1 GB | – | – | – | – |
| DeepSeek V4 Flash Vision Exp DeepSeek | MXFP4 | won't run | 155.8 GB | – | – | – | – |
| Devstral 2 123B Instruct 2512 Mistral AI | Q4_K_M | won't run | 73.3 GB | – | – | – | – |
| GLM 4.5 Z.ai | Q4_K_M | won't run | 205.2 GB | – | – | – | – |
| GLM 4.5V Z.ai | Q4_K_M | won't run | 61.4 GB | – | – | – | – |
| GLM 4.6 Z.ai | Q4_K_M | won't run | 204.4 GB | – | – | – | – |
| GLM 4.6V Z.ai | Q4_K_M | won't run | 67.8 GB | – | – | – | – |
| GLM 4.7 Z.ai | Q4_K_M | won't run | 205.2 GB | – | – | – | – |
| GLM 5 Z.ai | MXFP4 | won't run | 383.8 GB | – | – | – | – |
| GLM 5.1 Z.ai | MXFP4 | won't run | 421.4 GB | – | – | – | – |
| GLM 5.2 Z.ai | UD-Q4_K_M | won't run | 435.3 GB | – | – | – | – |
| GLM 5.3 Z.ai | Q8_0 | won't run | 747.8 GB | – | – | – | – |
| Kimi Dev 72B Moonshot AI | Q6_K | won't run | 63.2 GB | – | – | – | – |
| Kimi K2 Moonshot AI | Q4_K_M | won't run | 579.4 GB | – | – | – | – |
| Kimi K2 Instruct 0905 Moonshot AI | Q4_K_M | won't run | 579.9 GB | – | – | – | – |
| Kimi K2 Thinking Moonshot AI | Q4_K_M | won't run | 579.9 GB | – | – | – | – |
| Kimi K2.5 Moonshot AI | Q4_K_M | won't run | 579.9 GB | – | – | – | – |
| MiniMax M2 MiniMax | Q4_K_M | won't run | 131.5 GB | – | – | – | – |
| MiniMax M2.1 MiniMax | Q4_K_M | won't run | 131.5 GB | – | – | – | – |
| MiniMax M2.5 MiniMax | MXFP4 | won't run | 118.0 GB | – | – | – | – |
| MiniMax M3 MiniMax | MXFP4 | won't run | 241.4 GB | – | – | – | – |
| Mistral Medium 3.5 128B Mistral AI | Q4_K_M | won't run | 73.3 GB | – | – | – | – |
Specifications
From the manufacturer's published specifications; sources are linked where we have them.
- GPU
- GeForce RTX 4060 Ti 8GB
- Memory
- 8 GB GDDR6
- Memory bus
- 128-bit
- Memory bandwidth
- 288 GB/s
- FP16 compute
- 22.065 TFLOPS
- Software
- CUDA
- Board power
- 160 W
- PCIe generation
- Gen 4
- PCIe lanes
- x8
Compare with
Questions
- How much memory does the NVIDIA GeForce RTX 4060 Ti 8GB have for AI models?
- The NVIDIA GeForce RTX 4060 Ti 8GB has 8 GB of GDDR6 memory with 288 GB/s of bandwidth, which sets how fast it generates text.
- What is the best model the NVIDIA GeForce RTX 4060 Ti 8GB can run locally?
- Qwen 3.5 9B (Q5_K_M) fits fully in its memory at 8k context and generates at about 26 tok/s, an estimate from its memory bandwidth. 26 of the 129 models we track fit at that context.
- Can the NVIDIA GeForce RTX 4060 Ti 8GB run DeepSeek V4 Flash?
- No: even at UD-Q2_K_XL, DeepSeek V4 Flash needs about 92 GB at 8k context, more than the NVIDIA GeForce RTX 4060 Ti 8GB and system RAM can hold.
- How much does the NVIDIA GeForce RTX 4060 Ti 8GB cost in the US?
- The best new price for the NVIDIA GeForce RTX 4060 Ti 8GB in the US is $440 at eBay; used, it starts at $430 (asking price).
Speeds on this page are for 8k context. See the best hardware for local AI at every budget.