Will It Run AI

Can Phi 3 Medium 14B run on NVIDIA A800 80GB?

YES — Runs Great

B58Good
Estimated from fit model

Phi 3 Medium 14B needs ~20.8 GB VRAM. NVIDIA A800 80GB has 80.0 GB. With Q4_K_M quantization, expect ~177 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: HighStack: BasicBottleneck: Balanced
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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) — 20.8 GB, 190.0 tok/s, Runs well
20.8 GB required80.0 GB available
26% VRAM used

Fit status

Runs well

Decode

190.0 tok/s

TTFT

1019 ms

Safe context

128K

Memory

20.8 GB / 80.0 GB

Memory breakdown

Weights8.5 GB
KV Cache3.1 GB
Runtime1.2 GB
Headroom8.0 GB

See how fast it feels

See how fast it feelsPhi 3 Medium 14B on NVIDIA A800 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: 190.0 tok/s decode · 1.0s TTFT (warm) · 475 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
ChatBRuns well190.0 tok/s556 ms128K
CodingBRuns well176.7 tok/s1095 ms128K
Agentic CodingBRuns well190.0 tok/s1482 ms128K
ReasoningBRuns well190.0 tok/s1204 ms128K
RAGBRuns well190.0 tok/s1853 ms128K

Quantization options

How Phi 3 Medium 14B (14B params) fits at each quantization level on NVIDIA A800 80GB (80.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
5.5 GB
LowC51
Q3_K_S
3
6.9 GB
LowC51
NVFP4
4
7.8 GB
MediumC51
Q4_K_M
4
8.5 GB
MediumC51
Q5_K_M
5
10.1 GB
HighC51
Q6_K
6
11.5 GB
HighC51
Q8_0
8
15.0 GB
Very HighC52
F16Best for your GPU
16
28.7 GB
MaximumC54

Get started

Copy-paste commands to run Phi 3 Medium 14B on your machine.

Run

ollama run phi3:medium

Frequently asked questions

Can NVIDIA A800 80GB run Phi 3 Medium 14B?

Yes, NVIDIA A800 80GB can run Phi 3 Medium 14B with a B grade (Runs well). Expected decode speed: 176.7 tok/s.

How much VRAM does Phi 3 Medium 14B need?

Phi 3 Medium 14B (14B parameters) requires approximately 20.8 GB of memory with Q4_K_M quantization.

What is the best quantization for Phi 3 Medium 14B?

The recommended quantization for Phi 3 Medium 14B is Q4_K_M, which balances quality and memory efficiency.

What speed will Phi 3 Medium 14B run at on NVIDIA A800 80GB?

On NVIDIA A800 80GB, Phi 3 Medium 14B achieves approximately 176.7 tokens per second decode speed with a time-to-first-token of 1095ms using Q4_K_M quantization.

Can NVIDIA A800 80GB run Phi 3 Medium 14B for coding?

For coding workloads, Phi 3 Medium 14B on NVIDIA A800 80GB receives a B grade with 176.7 tok/s and 128K context.

What context window can Phi 3 Medium 14B use on NVIDIA A800 80GB?

On NVIDIA A800 80GB, Phi 3 Medium 14B can safely use up to 128K tokens of context. The model's official context limit is 128K, but available memory constrains the safe maximum.

See all results for NVIDIA A800 80GBSee all hardware for Phi 3 Medium 14B
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