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Calculated memory fit · performance is a separate section

Can Phi-4 run on NVIDIA RTX 5070 Ti 16 GB?

Yes. Calculated memory fit: Phi-4 can run entirely in this GPU’s usable VRAM at one or more supported quantizations.

Can it run?

Can it run?: Yes, full GPU fit (calculated estimate).
Full GPU fit?: Yes
Model: Phi-4 · 15B
GPU: NVIDIA RTX 5070 Ti 16 GB · 16 GB advertised

What else can NVIDIA RTX 5070 Ti 16 GB run? · Find other GPUs for Phi-4

Memory calculation

Breakdown for Q4 at 8K context, batch size 1. Calculator v1.0.0.

Model weights	8.6 GB
KV cache	1.6 GB
Runtime reserve	0.9 GB
Safety margin	0.5 GB
Required (estimated)	11.6 GB
GPU usable VRAM	14.4 GB

Result: FITS IN VRAM

Quantization table

Quantization	2K	4K	8K	16K
BF16	Offload	Offload	Offload	Offload
FP16	Offload	Offload	Offload	Offload
Q3	Fits	Fits	Fits	Fits
Q4	Fits	Fits	Fits	Fits
Q5	Fits	Fits	Fits	Limited context
Q6	Fits	Limited context	Limited context	Limited context
Q8	Offload	Offload	Offload	Offload

What fits entirely in VRAM?

Q3 at 16K context
Q3 at 2K context
Q3 at 4K context
Q3 at 8K context
Q4 at 16K context
Q4 at 2K context
Q4 at 4K context
Q4 at 8K context
Q5 at 2K context
Q5 at 4K context
Q5 at 8K context
Q6 at 2K context

What requires RAM offload?

Offload is shown only when the model does not fully fit in usable VRAM but stays within the modeled offload allowance.

Performance

Separate from memory fit. Runtime is llama.cpp · quantization bucket Q4 (GGUF Q4_0 maps to Q4). Workload is llama-bench pp512 / tg128 (short context, batch 1, full GPU offload). This is not a ranking and not a 8K–128K speed claim.

Model: Phi-4
GPU: NVIDIA RTX 5070 Ti 16 GB
Runtime: llama.cpp · CUDA · model 1.0.0
Decode: ~75 tok/s · Estimated · MEDIUM confidence (spread ~56 tok/s–~94 tok/s)
Prefill: unavailable for this workload
Time to first token: unavailable

decode_tps = GPU_efficiency × memory_bandwidth / model_weight_bytes; efficiency from same-gpu Llama 2 7B Q4_0 efficiency; param_ratio=2.18

Performance methodology · Performance explorer

Available graphics cards

These SKUs use this GPU chip. Amazon CTAs appear only for EXACT/HIGH matches. Absence of a price does not change the compatibility result above.

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ASUS

ASUS Prime -RTX5070TI-O16G NVIDIA GeForce RTX 5070 Ti 16 GB GDDR7

16 GB · Amazon EXACT

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ASUS

ASUS TUF Gaming TUF-RTX5070TI-O16G-GAMING NVIDIA GeForce RTX 5070 Ti 16 GB GDDR7

16 GB · Amazon EXACT

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MSI

MSI GeForce RTX 5070 Ti 16G VENTUS 3X OC NVIDIA 16 GB GDDR7

16 GB · Amazon EXACT

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GIGABYTE

GIGABYTE GeForce RTX 5070 Ti GAMING OC 16G Graphics Card

16 GB · Amazon EXACT

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ASUS

ASUS Prime -RTX5070TI-16G NVIDIA GeForce RTX 5070 Ti 16 GB GDDR7

16 GB · Amazon EXACT

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MSI

MSI GAMING GeForce RTX 5070 Ti 16G TRIO OC NVIDIA 16 GB GDDR7

16 GB · Amazon EXACT

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ASUS

ASUS ROG -STRIX-RTX5070TI-O16G-GAMING NVIDIA GeForce RTX 5070 Ti 16 GB GDDR7

16 GB · Amazon EXACT

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GIGABYTE

GIGABYTE GeForce RTX 5070 Ti WINDFORCE SFF 16G Graphics Card - 16GB GDDR7, 256bit, PCI-E 5.0, 2452 MHz Core Clock, 3 x DP 2.1b, 1 x HDMI 2.1b, NVIDIA DLSS 4, GV-N507TWF3-16GD

16 GB · Amazon EXACT

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GIGABYTE

GIGABYTE GeForce RTX 5070 Ti WINDFORCE OC SFF 16G Graphics Card

16 GB · Amazon EXACT

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Sources

Model: official config microsoft/phi-4 (main). GPU/product specs: Icecat. Compatibility: RigForAI calculator v1.0.0 estimated VRAM · Q8 at 8K: CPU_RAM_OFFLOAD_REQUIRED. Amazon: affiliate commerce match, not a spec source.