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URL: https://willitrunai.com/can-run/phi-4-reasoning-plus-14b-on-h100-80gb


Can Phi-4-reasoning-plus 14B run on NVIDIA H100 80GB?

YES — Runs Great

S87Excellent
Estimated from fit model

Phi-4-reasoning-plus 14B needs ~21.2 GB VRAM. NVIDIA H100 80GB has 80.0 GB. With Q4_K_M quantization, expect ~206 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) — 21.2 GB, 205.8 tok/s, Runs well
21.2 GB required80.0 GB available
27% VRAM used

Fit status

Runs well

Decode

205.8 tok/s

TTFT

941 ms

Safe context

33K

Memory

21.2 GB / 80.0 GB

Memory breakdown

Weights9.0 GB
KV Cache3.1 GB
Runtime1.2 GB
Headroom8.0 GB

See how fast it feels

See how fast it feelsPhi-4-reasoning-plus 14B on NVIDIA H100 80GB
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: 205.8 tok/s decode · 941ms TTFT (warm) · 515 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
ChatSRuns well205.8 tok/s513 ms33K
CodingSRuns well205.8 tok/s941 ms33K
Agentic CodingSRuns well205.8 tok/s1368 ms33K
ReasoningSRuns well205.8 tok/s1112 ms33K
RAGSRuns well205.8 tok/s1710 ms33K

Quantization options

How Phi-4-reasoning-plus 14B (14.699999809265137B params) fits at each quantization level on NVIDIA H100 80GB (80.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
5.7 GB
LowA79
Q3_K_S
3
7.2 GB
LowA80
NVFP4
4

Get started

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

Run

ollama run phi4-reasoning

Your hardware

More models your NVIDIA H100 80GB can run

ModelParamsGradeDecodeCapabilities
👁 Mistral
Devstral 2 123B Instruct
123BA28.9 tok/s
👁 Alibaba
Qwen3-Coder 30B A3B Instruct
30.5BS

Frequently asked questions

See all results for NVIDIA H100 80GBSee all hardware for Phi-4-reasoning-plus 14B
8.2 GB
Medium
A80
Q4_K_M
4
9.0 GB
MediumA80
Q5_K_M
5
10.6 GB
HighA80
Q6_K
6
12.1 GB
HighA80
Q8_0
8
15.7 GB
Very HighA81
F16Best for your GPU
16
30.1 GB
MaximumA83
425.5 tok/s
👁 Alibaba
Qwen 3.5 27B
27BS184.5 tok/s
👁 Alibaba
Qwen 3.6 27B
27BS185.1 tok/s
👁 Alibaba
Qwen 3.5 122B A10B
122BS85.5 tok/s