The best GPU for running Phi-4 14B (2026)
Ranked from live rental prices and computed VRAM fit, not opinion. Every card is judged at Q4_K_M — the quantisation most people actually run — at 8k context, so it's a fair comparison. A card that can't fit Phi-4 14Bat that quality isn't listed, because it could only run a crushed version.
Best value
NVIDIA GeForce RTX 3080 12GB
Most tokens/sec per rental dollar — ~77 tok/s at $0.029/hr.
Cheapest that runs it
NVIDIA GeForce RTX 3060 12GB
Lowest hourly rental that fits it — $0.026/hr, Q4_K_M.
No compromise
NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition
Fastest that fits — ~151 tok/s, 11% of its VRAM.
Every card that runs it, ranked
Best quantisation each card fits at 8k context, with the cheapest live rental and a bandwidth-derived throughput estimate. Sorted by tokens/sec per dollar.
| GPU | VRAM | VRAM used | ~tok/s | Cheapest rental | tok/s per $ |
|---|---|---|---|---|---|
| NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition | 96 GB | 11 GB11% | ~151 | $1.690 | 89 |
| NVIDIA RTX PRO 6000 Blackwell Workstation Edition | 96 GB | 11 GB11% | ~151 | — | — |
| NVIDIA GeForce RTX 3080 12GB | 12 GB | 11 GB89% | ~77 | $0.029 | 2663 |
| NVIDIA GeForce RTX 5090 | 32 GB | 11 GB33% | ~151 | $0.058 | 2616 |
| NVIDIA GeForce RTX 3080 Ti | 12 GB | 11 GB89% | ~77 | $0.062 | 1237 |
| NVIDIA GeForce RTX 3060 12GB | 12 GB | 11 GB89% | ~30 | $0.026 | 1173 |
| NVIDIA GeForce RTX 5070 Ti | 16 GB | 11 GB66% | ~76 | $0.068 | 1105 |
| NVIDIA GeForce RTX 3090 Ti | 24 GB | 11 GB44% | ~85 | $0.077 | 1103 |
| NVIDIA RTX A5000 | 24 GB | 11 GB44% | ~65 | $0.074 | 873 |
| NVIDIA GeForce RTX 4070 Ti SUPER | 16 GB | 11 GB66% | ~57 | $0.069 | 823 |
| NVIDIA GeForce RTX 5080 | 16 GB | 11 GB66% | ~81 | $0.109 | 744 |
| NVIDIA GeForce RTX 4090 | 24 GB | 11 GB44% | ~85 | $0.134 | 633 |
How this ranking is made — and its limit
Fit and throughput are computed from Phi-4 14B's own configuration with the engine behind our cost-to-run page (bits-per-weight validated to 0.7% median error). Rental prices are the cheapest live figure across the providers we track, last updated Wed, 22 Jul 2026 11:20:07 GMT.
The value column ranks renting, because that's what we can price precisely. If you're buyinga card, the fit and throughput columns are exactly what you need — but we don't publish a purchase-price value ranking, because we don't have verified street prices and won't invent them. For the buy-vs-rent decision itself, see the guides below.
Tokens/sec is a bandwidth-derived estimate, not a benchmark — we don't run our own hardware tests (editorial policy).
Check it yourself
See exactly what fits, at any context length
Running Phi-4 14B: common questions
How much VRAM do you need to run Phi-4 14B?
Can an RTX 4090 run Phi-4 14B?
Can an RTX 3090 run Phi-4 14B?
Can an RTX 4060 Ti 16GB run Phi-4 14B?
What's the cheapest way to run Phi-4 14B?
Before you buy
RTX 5090 vs two RTX 3090s
Two 3090s give you 48 GB but not double the speed for chat — llama.cpp's default multi-GPU mode makes the cards take turns. What the benchmarks actually show.
Cheapest way to serve Llama 70B
"Cheapest" flips on duty cycle and concurrency — and in Europe the electricity bill alone can approach the cost of just renting. Plus the config defaults that silently break a 16k deployment.
What --n-cpu-moe actually does
The trick that makes MoE models 5× faster — except it usually makes them slower, and the famous speedup only happens when the model didn't fit in the first place.