Qwen 2.5 14B AWQ on the RTX 5060 Ti 16GB delivers stronger reasoning than 7B class at mid-tier cost on our dedicated hosting.
Contents
Throughput
Qwen 2.5 14B AWQ on 5060 Ti:
- Batch 1: ~44 t/s
- Batch 8: ~240 t/s aggregate
- Batch 16: ~380 t/s aggregate
Monthly Capacity
At 50% utilisation on batch 8:
- Output tokens: ~310M/month
- Input tokens (3:1): ~930M/month
- Blended: ~1.25B tokens/month
Lower total volume than 7B class on the same card due to per-token compute cost, but quality is higher.
Vs API
| API | Blended Rate | Your Traffic Cost |
|---|---|---|
| Together Qwen 14B | ~$0.30/M | ~$375/month |
| Fireworks Qwen | ~$0.30/M | ~$375/month |
| OpenAI GPT-4o-mini (quality equivalent on some tasks) | $0.15 in / $0.60 out | ~$326/month |
Break-Even
Dedicated 5060 Ti at ~£300/month (~$380). Break-even versus Together Qwen hits around 50-60% utilisation. Above that, dedicated wins.
For production Qwen workloads, dedicated is competitive on cost and superior on:
- Data residency (UK)
- No rate limits
- Fine-tune friendly (deploy custom QLoRA adapters)
- Combined stack (embedder, reranker, Whisper on same card)
Why 14B
Qwen 14B scores ~77 MMLU versus 66-71 for 7-8B models – a meaningful jump in reasoning quality. For workloads where quality matters more than raw concurrency, the 14B is the right pick at the 5060 Ti tier.
For much higher concurrency on 14B, step up to 5080.
Qwen 14B on Blackwell
Stronger reasoning than 7B class, mid-tier cost. UK dedicated hosting.
Order the RTX 5060 Ti 16GBSee also: deployment guide, benchmark.
