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The 5060 Ti at £119/mo and the 5090 at £399/mo are 2.1× the cost. The capability multiplier varies by workload: 2× for FP8 7B chatbots, 4× for 14B+ FP16, ∞ for 70B-class models.
Upgrade from 5060 Ti to 5090 when: 1) you need 14B+ FP16, 2) p99 TTFT regularly exceeds 1s on the 5060 Ti, 3) you want to stack two models on one card, 4) traffic exceeds ~30 concurrent users. Otherwise stay on the 5060 Ti.
What you get
| Spec | RTX 5060 Ti 16 GB | RTX 5090 32 GB | Delta |
|---|---|---|---|
| VRAM | 16 GB | 32 GB | +100% |
| Memory bandwidth | 448 GB/s | 1,792 GB/s | +300% |
| CUDA cores | 4,608 | 21,760 | +372% |
| FP16 TFLOPS | ~24 | ~210 | +775% |
| FP8 TOPS | ~184 | ~838 | +355% |
| Monthly cost | £119 | £399 | +112% |
The 5090 is dramatically more capable on raw compute. The pricing is 2× but the throughput uplift is 3-5× depending on workload.
Upgrade trigger conditions
- p99 TTFT > 1.0s sustained on 5060 Ti — concurrent batching is the bottleneck
- You want 14B+ FP16 — 5060 Ti can't hold that
- You want voice agent (Whisper + LLM + TTS on one card) — 16 GB too tight
- Traffic regularly >30 concurrent users — 5060 Ti tops out
- You want speculative decoding with native FP4 — 5090's FP4 hardware
Verdict
For 7B chatbots at moderate concurrency, stay on the 5060 Ti. For 14B+, voice agents, multi-model stacks, or high-concurrency production, upgrade. The capability gain typically justifies the 2× cost.
Bottom line
Set Prometheus alerts on TTFT and GPU memory util — they will tell you when to upgrade. See when to upgrade.
