Phi-4 14B on NVIDIA GeForce RTX 4060 Ti 16GB
Measured this month.
Measurement
- tok/s
- 28.3
- TTFT
- 195 ms
- VRAM used
- 9.4 GB
- RAM used
- 1.8 GB
- Power
- 132 W
- Quant
- Q4_K_M
- Context
- 8K
- Run date
- 2026-05-04
- Source
- community
RTX 4060 Ti 16GB is the budget consumer card that justifies its premium over the 8GB SKU specifically for 13-14B class models. Phi-4 14B Q4_K_M fits in ~9.5 GB with comfortable KV-cache headroom for 8K context. Power draw is ~135 W under load — under half a 4090 — making this the right pick for power-constrained homelab nodes. Community range: 25-32 tok/s; numbers vary with sampler config and CUDA driver version.
Why this confidence tier?
Confidence is rule-based. Every factor below contributed to the tier. We never expose a single numeric score; the tier label is auditable through this explanation alone.
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Cohort intelligence
How this measurement compares to the rest of the corpus. Only comparable rows (same model + hardware first, with relaxations labelled) are used. We never average across runtimes or quant formats unless explicitly told to.
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<a href="https://runlocalai.co/benchmarks/330" rel="noopener">RunLocalAI: Phi-4 14B on NVIDIA GeForce RTX 4060 Ti 16GB — 28.3 tok/s</a>
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