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URL: https://willitrunai.com/can-run/phi-4-14b-on-h20-96gb


Can Phi-4 14B run on NVIDIA H20 96GB?

YES — Runs Great

A79Great
Estimated from fit model

Phi-4 14B needs ~22.4 GB VRAM. NVIDIA H20 96GB has 96.0 GB. With Q4_K_M quantization, expect ~196 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: HighStack: BasicBottleneck: Balanced
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) — 22.4 GB, 196.0 tok/s, Runs well
22.4 GB required96.0 GB available
23% VRAM used

Fit status

Runs well

Decode

196.0 tok/s

TTFT

988 ms

Safe context

16K

Memory

22.4 GB / 96.0 GB

Memory breakdown

Weights8.5 GB
KV Cache3.1 GB
Runtime1.2 GB
Headroom9.6 GB

See how fast it feels

See how fast it feelsPhi-4 14B on NVIDIA H20 96GB
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: 196.0 tok/s decode · 988ms TTFT (warm) · 490 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

No major red flags

This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.

Best improvement path

Performance by workload

WorkloadGradeFitDecodeTTFTContext
ChatARuns well196.0 tok/s539 ms16K
CodingARuns well196.0 tok/s988 ms16K
Agentic CodingARuns well196.0 tok/s1437 ms16K
ReasoningARuns well196.0 tok/s1167 ms16K
RAGARuns well196.0 tok/s1796 ms16K

Quantization options

How Phi-4 14B (14B params) fits at each quantization level on NVIDIA H20 96GB (96.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
5.5 GB
LowA71
Q3_K_S
3
6.9 GB
LowA71
NVFP4
4

Get started

Copy-paste commands to run Phi-4 14B on your machine.

Run

ollama run phi4

Your hardware

More models your NVIDIA H20 96GB can run

ModelParamsGradeDecodeCapabilities
👁 Mistral
Devstral 2 123B Instruct
123BS47 tok/s
👁 Alibaba
Qwen3-Coder 30B A3B Instruct
30.5BS

Frequently asked questions

See all results for NVIDIA H20 96GBSee all hardware for Phi-4 14B
7.8 GB
Medium
A71
Q4_K_M
4
8.5 GB
MediumA71
Q5_K_M
5
10.1 GB
HighA71
Q6_K
6
11.5 GB
HighA71
Q8_0
8
15.0 GB
Very HighA72
F16Best for your GPU
16
28.7 GB
MaximumA73
489.9 tok/s
👁 Alibaba
Qwen 3.5 27B
27BS212.5 tok/s
👁 Alibaba
Qwen 3.6 27B
27BS213.1 tok/s
👁 Alibaba
Qwen 3.5 122B A10B
122BS130.3 tok/s