Will It Run AI

Can Phi 4 reasoning vision 15B run on Radeon Pro W7800 32GB?

YES — Runs Great

C49Usable
Estimated from fit model

Phi 4 reasoning vision 15B needs ~15.0 GB VRAM. Radeon Pro W7800 32GB has 32.0 GB. With Q4_K_M quantization, expect ~37 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: MediumStack: 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) 15.0 GB, 37.1 tok/s, Runs well
15.0 GB required32.0 GB available
47% VRAM used

Fit status

Runs well

Decode

37.1 tok/s

TTFT

5213 ms

Safe context

171K

Memory

15.0 GB / 32.0 GB

Memory breakdown

Weights9.2 GB
KV Cache1.8 GB
Runtime0.9 GB
Headroom3.2 GB

See how fast it feels

See how fast it feelsPhi 4 reasoning vision 15B on Radeon Pro W7800 32GB
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: 37.1 tok/s decode · 5.2s TTFT (warm) · 93 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
ChatCRuns well37.1 tok/s2843 ms171K
CodingCRuns well37.1 tok/s5213 ms171K
Agentic CodingCRuns well37.1 tok/s7582 ms171K
ReasoningCRuns well37.1 tok/s6160 ms171K
RAGCRuns well37.1 tok/s9477 ms171K

Quantization options

How Phi 4 reasoning vision 15B (15B params) fits at each quantization level on Radeon Pro W7800 32GB (32.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
5.9 GB
LowC44
Q3_K_S
3
7.4 GB
LowC45
NVFP4
4
8.4 GB
MediumC45
Q4_K_M
4
9.2 GB
MediumC45
Q5_K_M
5
10.8 GB
HighC46
Q6_K
6
12.3 GB
HighC47
Q8_0Best for your GPU
8
16.1 GB
Very HighC49
F16
16
30.7 GB
MaximumF0

Get started

Copy-paste commands to run Phi 4 reasoning vision 15B on your machine.

Run

lms load hf-jamesburton--phi-4-reasoning-vision-15b-gguf && lms server start

升级选项

能流畅运行 Phi 4 reasoning vision 15B 的硬件

Frequently asked questions

Can Radeon Pro W7800 32GB run Phi 4 reasoning vision 15B?

Yes, Radeon Pro W7800 32GB can run Phi 4 reasoning vision 15B with a C grade (Runs well). Expected decode speed: 37.1 tok/s.

How much VRAM does Phi 4 reasoning vision 15B need?

Phi 4 reasoning vision 15B (15B parameters) requires approximately 15.0 GB of memory with Q4_K_M quantization.

What is the best quantization for Phi 4 reasoning vision 15B?

The recommended quantization for Phi 4 reasoning vision 15B is Q4_K_M, which balances quality and memory efficiency.

What speed will Phi 4 reasoning vision 15B run at on Radeon Pro W7800 32GB?

On Radeon Pro W7800 32GB, Phi 4 reasoning vision 15B achieves approximately 37.1 tokens per second decode speed with a time-to-first-token of 5213ms using Q4_K_M quantization.

Can Radeon Pro W7800 32GB run Phi 4 reasoning vision 15B for coding?

For coding workloads, Phi 4 reasoning vision 15B on Radeon Pro W7800 32GB receives a C grade with 37.1 tok/s and 171K context.

What context window can Phi 4 reasoning vision 15B use on Radeon Pro W7800 32GB?

On Radeon Pro W7800 32GB, Phi 4 reasoning vision 15B can safely use up to 171K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.

See all results for Radeon Pro W7800 32GBSee all hardware for Phi 4 reasoning vision 15B
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