The RTX 4060 8GB and RTX 5060 Ti 16GB sit in the same tier segment but deliver very different AI performance on our hosting.
Contents
Specs
| Spec | 5060 Ti 16GB | 4060 8GB |
|---|---|---|
| Arch | Blackwell | Ada Lovelace |
| CUDA cores | 4,608 | 3,072 |
| VRAM | 16 GB | 8 GB |
| Bandwidth | 448 GB/s | 272 GB/s |
| FP8 tensor cores | 5th gen native | 4th gen native |
| TDP | 180 W | 115 W |
LLM Decode
| Model | 5060 Ti t/s | 4060 t/s |
|---|---|---|
| Phi-3-mini FP8 | 285 | 180 |
| Llama 3 8B FP8 | 112 | 65 (tight VRAM) |
| Llama 3 8B AWQ INT4 | 135 | 85 |
| Qwen 2.5 14B AWQ | 70 | OOM |
What Fits
- 4060 8GB: Phi-3-mini FP8, Llama 3 8B AWQ at 8k context only, no 14B at all
- 5060 Ti 16GB: Llama 3 8B FP8 at 32k, Qwen 2.5 14B AWQ at 16k, Gemma 2 9B, Llama Vision 11B
Verdict
The 5060 Ti 16GB is the minimum viable card for mainstream LLM hosting in 2026. The 4060 8GB is useful only for small models (<4B) or image-gen workloads. If your use case involves Llama/Qwen/Gemma at production quality, go straight to 16 GB.
For ultimate budget, see 5060 Ti vs 5060 8GB – the 5060 Ti is roughly 2x the 5060 for LLM work thanks to VRAM.
Blackwell 16GB vs Ada 8GB
16 GB opens every mainstream LLM. UK dedicated hosting.
Order the RTX 5060 Ti 16GBSee also: vs 4060 Ti, vs 3090, vs 5080, vs 5060 8GB.
