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URL: https://willitrunai.com/can-run/phi-3-medium-14b-on-rtx-4070-laptop-8gb

⇱ Phi 3 Medium 14B on RTX 4070 Laptop 8GB? No — Alternatives

Can Phi 3 Medium 14B run on RTX 4070 Laptop 8GB?

NO — Won't Fit

F0Won't run
○Estimated from fit model

Phi 3 Medium 14B needs ~13.6 GB but RTX 4070 Laptop 8GB only has 8.0 GB. Try a smaller quantization or lighter model.

Runtime: OllamaCapacity: No fitBandwidth: LowStack: BasicBottleneck: Memory capacity
Share:

Operating mode

Choose the run profile you care about

Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.

Current mode

Balanced

Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.

Capabilities:

Select quantization to explore

Q4_K_M (Medium quality) — 13.6 GB, exceeds 8.0 GB available
13.6 GB required8.0 GB available
170% VRAM needed

5.6 GB over capacity — needs offload or smaller quantization

Fit status

Too heavy

Decode

6.0 tok/s

TTFT

32165 ms

Safe context

4K

Memory

13.6 GB / 8.0 GB

Offload

40%

Memory breakdown

Weights8.5 GB
KV Cache3.1 GB
Runtime1.2 GB
Headroom0.8 GB

See how fast it feels

With memory offload — actual speed may be lower
See how fast it feelsPhi 3 Medium 14B on RTX 4070 Laptop 8GB
1st promptCold start — includes initialization
>Solve: If a train travels at 60 mph for 2.5 hours, how far does it go?
Let me work through this step by step. Given information: - Speed = 60 mph (miles per hour) - Time = 2.5 hours Formula: Distance = Speed x Time Calculation: Distance = 60 mph x 2.5 h = 150 miles The train travels 150 miles. Double-check: at 60 mph the train covers 60 miles each hour. In half an hour it covers 30 miles. So in 2.5 hours: 60 + 60 + 30 = 150 miles. Confirmed.
2nd promptWarm — model ready, no init overhead
>What if the train stops for 20 minutes halfway?
The stop doesn't change the total distance covered while moving, but it affects total trip time. Breakdown: - First half: 1.25 hours at 60 mph = 75 miles - Stop: 20 minutes (no distance) - Second half: 1.25 hours at 60 mph = 75 miles Total distance: 150 miles (same) Total time: 2.5 h + 0.33 h = 2.83 hours Average speed: 150 / 2.83 = 53 mph The distance stays the same but average speed drops to 53 mph because of the stop.
Estimated: 6.0 tok/s decode · 32.2s TTFT (warm) · 15 tok/s prefill

What limits this setup

Usable VRAM is the main blocker for this model.

Not enough usable memory

The model needs 13.6 GB, but this setup only exposes 8.0 GB of usable VRAM.

Best improvement path

Add more VRAM headroom

The first useful upgrade is more dedicated VRAM so you can fit the model without shrinking context or dropping to a much lower quant.

Performance by workload

WorkloadGradeFitDecodeTTFTContext
ChatFToo heavy7.7 tok/s13654 ms4K
CodingFToo heavy6.0 tok/s32165 ms4K
Agentic CodingFToo heavy3.9 tok/s71661 ms4K
ReasoningFToo heavy6.0 tok/s38013 ms4K
RAGFToo heavy3.9 tok/s89576 ms4K

Quantization options

How Phi 3 Medium 14B (14B params) fits at each quantization level on RTX 4070 Laptop 8GB (8.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
5.5 GB
LowF0
Q3_K_S
3
6.9 GB
LowF0
NVFP4
4
7.8 GB
MediumF0
Q4_K_M
4
8.5 GB
MediumF0
Q5_K_M
5
10.1 GB
HighF0
Q6_K
6
11.5 GB
HighF0
Q8_0
8
15.0 GB
Very HighF0
F16
16
28.7 GB
MaximumF0

Upgrade options

Hardware that runs Phi 3 Medium 14B well

👁 NVIDIA
RTX 3060 12GBBest value
12 GB VRAM (+4)360 GB/s (+104)
C
Makes the model fit on the accelerator instead of staying completely out of reach.16.2 tok/s decode

Makes the model fit on the accelerator instead of staying completely out of reach.

Raises estimated decode speed by about 170%.

~$329 MSRP

👁 NVIDIA
RTX 5060 Ti 16GBBudget pick
16 GB VRAM (+8)448 GB/s (+192)
B
Makes the model fit on the accelerator instead of staying completely out of reach.35 tok/s decode

Makes the model fit on the accelerator instead of staying completely out of reach.

Removes host-memory offload, which is usually the single biggest latency and throughput win.

~$449 MSRP

👁 NVIDIA
RTX 4060 Ti 16GBNVIDIA upgrade
16 GB VRAM (+8)288 GB/s (+32)
B
Makes the model fit on the accelerator instead of staying completely out of reach.26.5 tok/s decode

Makes the model fit on the accelerator instead of staying completely out of reach.

Removes host-memory offload, which is usually the single biggest latency and throughput win.

~$499 MSRP

Frequently asked questions

See all results for RTX 4070 Laptop 8GBSee all hardware for Phi 3 Medium 14B