GeForce RTX 5060 Ti 16GB Price & Used Prices: Which Local LLMs Can It Run?
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NVIDIA's RTX 5060 Ti 16GB (2025) is a 180W entry gaming card that fits 12B-class models even at 8-bit. vLLM needs CUDA 12.8 or newer to see it.
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GeForce RTX 5060 Ti 16GB price history
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Full GeForce RTX 5060 Ti 16GB specifications
- Memory16 GB · GDDR7
- Bandwidth448 GB/s
- FP16 / BF1694.9 TFLOPS
- FP8 / INT8189.8 / 189.8 TOPS
- Bus width
- 128-bit
- Architecture
- Blackwell (GB206)
- Cores
- 4,608
- Tensor cores
- 144
- Ecosystem
- CUDA
- Interface
- PCIe 5.0 x8
- NVLink
- Not supported
- Power
- 180 W
- Power connector
- 1× 8-pin / 16-pin 12V-2x6
- Type
- Consumer
- Launch date
- Apr 16, 2025
- MSRP
- $429
Best GeForce RTX 5060 Ti 16GB deals on eBay
Deals from trusted eBay sellers, picked by our rules. Shop with confidence.
As an eBay Partner, VRAMGlass may be compensated if you buy through the eBay links on this page. The price you pay stays the same.
Used(Factory Refurbished) ASUS RTX 5060 Ti 16GB DUAL-RTX5060TI-O16G Video CardTop Rated$720Buy on eBay
UsedPNY Nvidia GeForce RTX 5060 Ti 16GB GPU Graphics Card Free Shipping$730Buy on eBay
UsedASUS Dual GeForce RTX 5060 Ti 16GB GDDR7 PCI Express 5.0 x8 Graphics Card GPU$750+$10 shippingBuy on eBay
UsedMSI - NVIDIA GeForce RTX 5060 Ti 16G VENTUS 2X OC Express Gen 5 Graphics Card$775+ shippingBuy on eBay
UsedGIGABYTE RTX 5060 Ti 16GB GDDR7 Graphics Card GV-N506TGAMING OC-16GDTop Rated$780Buy on eBay
UsedGIGABYTE GeForce RTX 5060 Ti EAGLE OC ICE 16G Graphics Card Tested Free Shipping$780Buy on eBay
What LLMs can a single GeForce RTX 5060 Ti 16GB run?
One 5060 Ti 16GB runs up to 12B best at 4-bit, and 8-bit fits too. 27B-class at 4-bit just misses 16GB; 30B-class MoE at 2-bit tops 100 tokens/s.
| Model | Size | Runs? | Speed t/s | Max context |
|---|---|---|---|---|
 Gemma 4 E4B8B | 3.8 GB | Runs | 78.8 | 128K |
 Qwen3.5 9B9.7B | 4.1 GB | Runs | 72.9 | 256K |
| Gemma 4 12B12B | 4.7 GB | Runs | 63.5 | 256K |
| Gemma 4 26B A4B25.2B (3.8B active) | 10.5 GB | Runs | 101.5 | 256K |
| Qwen3.6 27B27.8B | 11.8 GB | Runs | 27.4 | 64K |
| Qwen3.8 27B27.8B | 9.8 GB | Runs | 32.6 | 93K |
 GLM 4.7 Flash30B (3B active) | 11.9 GB | Runs | 113.7 | 75K |
| Gemma 4 31B30.7B | 11.8 GB | Runs | 26.4 | 41K |
| Qwen3.6 35B A3B36B (3B active) | 12.3 GB | Runs | 126.1 | 181K |
| Model | Size | Runs? | Speed t/s | Max context |
|---|---|---|---|---|
| Gemma 4 E4B8B | 5 GB | Runs | 61.8 | 128K |
| Qwen3.5 9B9.7B | 5.7 GB | Runs | 54.4 | 256K |
| Gemma 4 12B12B | 7.1 GB | Runs | 44 | 256K |
| Gemma 4 26B A4B25.2B (3.8B active) | 16.9 GB | Needs RAM offload | 35.1 | 256K |
| Qwen3.6 27B27.8B | 16.8 GB | Too big | — | — |
| Qwen3.8 27B27.8B | 16.5 GB | Too big | — | — |
| GLM 4.7 Flash30B (3B active) | 18.3 GB | Needs RAM offload | 34.7 | 198K |
| Gemma 4 31B30.7B | 18.3 GB | Too big | — | — |
| Qwen3.6 35B A3B36B (3B active) | 22.1 GB | Needs RAM offload | 47.4 | 256K |
| Model | Size | Runs? | Speed t/s | Max context |
|---|---|---|---|---|
| Gemma 4 E4B8B | 8.2 GB | Runs | 39.2 | 128K |
| Qwen3.5 9B9.7B | 9.5 GB | Runs | 34 | 196K |
| Gemma 4 12B12B | 12.7 GB | Runs | 25.6 | 183K |
| Gemma 4 26B A4B25.2B (3.8B active) | 26.9 GB | Needs RAM offload | 23.7 | 256K |
| Qwen3.6 27B27.8B | 28.6 GB | Too big | — | — |
| Qwen3.8 27B27.8B | 29 GB | Too big | — | — |
| GLM 4.7 Flash30B (3B active) | 31.8 GB | Needs RAM offload | 21.7 | 198K |
| Gemma 4 31B30.7B | 32.6 GB | Too big | — | — |
| Qwen3.6 35B A3B36B (3B active) | 36.9 GB | Needs RAM offload | 31.3 | 256K |
RunsFits fully in VRAM; speed is estimated from VRAM bandwidth.
Needs RAM offloadMoE only: expert weights sit in system RAM, so speed is estimated from 70 GB/s RAM bandwidth.
Too bigWon’t fit on one card at this quantization, even with RAM offload.
Full calculation rules are on the Methodology page.
Who it suits
Good fit
- Running 12B models at 8-bit
Gemma 4 12B at 8-bit (12.7 GB) fits entirely on the card with 183K of context, at about 26 tokens/s, which a 12GB card can't do
- Choosing between it and the 4060 Ti 16GB
The same 16GB, only 15W more power, and dense models run 50% faster
- Your case and power supply are limited
The card draws 180W, the official spec calls for a single 8-pin connector, and NVIDIA recommends a 600W system power supply
Not a good fit
- Running Qwen3.8 27B at 4-bit
At 16.5 GB it is more than 16GB, so you have to drop to 2-bit, at about 33 tokens/s
- Running 30B-class MoE models at 4-bit
The experts have to go into system RAM, so speed depends on RAM bandwidth; Qwen3.6 35B A3B runs at about 47 tokens/s, about the same as on the 4060 Ti 16GB
Before you buy
Don't end up with the 8GB version
If a listing just says “5060 Ti”, ask about the VRAM. The 8GB and 16GB versions use the same chip and differ only in memory capacity, but for running models the gap is huge. NVIDIA made no Founders Edition; both versions are partner cards.
PCIe 5.0 x8 on an older platform
It uses only 8 PCIe lanes. On a PCIe 5.0 motherboard that gives it the same bandwidth as 4.0 x16; on a PCIe 4.0 board it drops to 4.0 x8, and on PCIe 3.0 to just 3.0 x8. The impact is smaller than you might think: TechSpot tested the 16GB version in games on PCIe 3.0, and frame rates barely changed as long as VRAM was sufficient. The same goes for running models: once the weights are in VRAM, little traffic goes over PCIe.
The 50 series needs recent software
The 50 series is a new architecture, and software has to be compiled with CUDA 12.8 or later to recognize it; PyTorch provides matching prebuilt packages starting with 2.7. For llama.cpp and Ollama, just install a recent version. If you use an old Docker image or build vLLM yourself, check the CUDA version first, or you will get an error saying sm_120 is unsupported.
Compared with similar GPUs
GeForce RTX 5060 Ti 16GB vs GeForce RTX 4060 Ti 16GB, GeForce RTX 5070, and GeForce RTX 5070 Ti: price, VRAM, bandwidth, compute and local LLM speed compared.
| Spec | GeForce RTX 5060 Ti 16GB | GeForce RTX 4060 Ti 16GB | GeForce RTX 5070 | GeForce RTX 5070 Ti |
|---|---|---|---|---|
| Memory | 16 GB | 16 GBSame | 12 GB25% less | 16 GBSame |
| Bandwidth | 448 GB/s | 288 GB/s36% lower | 672 GB/s50% higher | 896 GB/s100% higher |
| BF16 / FP16 compute | 95 TFLOPS | 88 TFLOPS7% lower | 124 TFLOPS30% higher | 176 TFLOPS85% higher |
| INT8 compute | 190 TOPS | 177 TOPS7% lower | 247 TOPS30% higher | 352 TOPS85% higher |
| Qwen3.8 27B speed (2-bit) | 32.6 t/s | 21.3 t/s35% slower | 47.8 t/s47% faster | 62.3 t/s91% faster |
| Largest dense model (4-bit) | 23B | 23BSame | 16B30% less | 23BSame |
| Power | 180 W | 165 W8% lower | 250 W39% higher | 300 W67% higher |
| Interface | PCIe 5.0 x8 | PCIe 4.0 x8 | PCIe 5.0 x16 | PCIe 5.0 x16 |
| Released | 2025-04 | 2023-07 | 2025-03 | 2025-02 |
| eBay median |
As an eBay Partner, VRAMGlass may be compensated if you buy through the eBay links on this page. The price you pay stays the same.
GeForce RTX 5060 Ti 16GB rental price per hour
On Vast.ai, the GeForce RTX 5060 Ti 16GB rents for $0.17 per hour on demand, about $41/month at 8 hours a day. Buying one (eBay median $845) pays off in about 4.3 years, 2.2 years or 9 months at 4, 8 or 24 hours a day.
| Option | Price | 4 h/day | 8 h/day | 24 h/day | View |
|---|---|---|---|---|---|
 Vast.aiRentUpdated 1 hr. ago | $0.17/hr | $20/mo | $41/mo | $122/mo | Rent |
 eBayUpdated 3 hr. ago | $845 | Payback ~4.3 yrsPower $4/mo | Payback ~2.2 yrsPower $8/mo | Payback ~9 moPower $24/mo | Buy |
Break-even uses the US residential average ($0.18/kWh) and 180 W rated power, excluding resale value and the rest of the build.
Rental links are referral links: we may receive a commission or credit if you sign up through them. As an eBay Partner, VRAMGlass may be compensated if you buy through the eBay links on this page. The price you pay stays the same.
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