Will It Run AI

Can Phi-4-reasoning-plus 14B run on Radeon Pro W7900 48GB?

YES — Runs Great

S88Excellent
Estimated from fit model

Phi-4-reasoning-plus 14B needs ~17.7 GB VRAM. Radeon Pro W7900 48GB has 48.0 GB. With Q4_K_M quantization, expect ~61 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: HighStack: StandardBottleneck: 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) — 17.7 GB, 61.1 tok/s, Runs well
17.7 GB required48.0 GB available
37% VRAM used

Fit status

Runs well

Decode

61.1 tok/s

TTFT

3168 ms

Safe context

33K

Memory

17.7 GB / 48.0 GB

Memory breakdown

Weights9.0 GB
KV Cache3.1 GB
Runtime0.9 GB
Headroom4.8 GB

See how fast it feels

See how fast it feelsPhi-4-reasoning-plus 14B on Radeon Pro W7900 48GB
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: 61.1 tok/s decode · 3.2s TTFT (warm) · 153 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 well61.1 tok/s1728 ms33K
CodingSRuns well61.1 tok/s3168 ms33K
Agentic CodingSRuns well61.1 tok/s4608 ms33K
ReasoningSRuns well61.1 tok/s3744 ms33K
RAGSRuns well61.1 tok/s5760 ms33K

Quantization options

How Phi-4-reasoning-plus 14B (14.699999809265137B params) fits at each quantization level on Radeon Pro W7900 48GB (48.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
5.7 GB
LowA82
Q3_K_S
3
7.2 GB
LowA82
NVFP4
4
8.2 GB
MediumA82
Q4_K_M
4
9.0 GB
MediumA82
Q5_K_M
5
10.6 GB
HighA83
Q6_K
6
12.1 GB
HighA83
Q8_0
8
15.7 GB
Very HighA84
F16Best for your GPU
16
30.1 GB
MaximumS88

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 Radeon Pro W7900 48GB can run

ModelParamsGradeDecodeCapabilities
AlibabaQwen3-Coder 30B A3B Instruct30.5BS77.1 tok/s
AlibabaQwen 3.5 27B27BS33.4 tok/s
AlibabaQwen 3.6 27B27BS23.9 tok/s
AlibabaQwen 3.6 35B A3B35BS64.8 tok/s
AlibabaQwen3-VL 30B A3B Instruct30BS79.7 tok/s

Frequently asked questions

Can Radeon Pro W7900 48GB run Phi-4-reasoning-plus 14B?

Yes, Radeon Pro W7900 48GB can run Phi-4-reasoning-plus 14B with a S grade (Runs well). Expected decode speed: 61.1 tok/s.

How much VRAM does Phi-4-reasoning-plus 14B need?

Phi-4-reasoning-plus 14B (14.699999809265137B parameters) requires approximately 17.7 GB of memory with Q4_K_M quantization.

What is the best quantization for Phi-4-reasoning-plus 14B?

The recommended quantization for Phi-4-reasoning-plus 14B is Q4_K_M, which balances quality and memory efficiency.

What speed will Phi-4-reasoning-plus 14B run at on Radeon Pro W7900 48GB?

On Radeon Pro W7900 48GB, Phi-4-reasoning-plus 14B achieves approximately 61.1 tokens per second decode speed with a time-to-first-token of 3168ms using Q4_K_M quantization.

Can Radeon Pro W7900 48GB run Phi-4-reasoning-plus 14B for coding?

For coding workloads, Phi-4-reasoning-plus 14B on Radeon Pro W7900 48GB receives a S grade with 61.1 tok/s and 33K context.

What context window can Phi-4-reasoning-plus 14B use on Radeon Pro W7900 48GB?

On Radeon Pro W7900 48GB, Phi-4-reasoning-plus 14B can safely use up to 33K tokens of context. The model's official context limit is 33K, but available memory constrains the safe maximum.

See all results for Radeon Pro W7900 48GBSee all hardware for Phi-4-reasoning-plus 14B
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