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URL: https://willitrunai.com/can-run/phi-4-mini-4b-on-arc-a380-6gb

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Can Phi 4 Mini 4B run on Intel Arc A380 6GB?

YES — Tight Fit

A72Great
○Estimated from fit model

Phi 4 Mini 4B needs ~5.4 GB VRAM. Intel Arc A380 6GB has 6.0 GB. With Q4_K_M quantization, expect ~37 tok/s.

Runtime: llama.cppCapacity: TightBandwidth: Very lowStack: StandardBottleneck: Memory bandwidth
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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) — 5.4 GB, 40.2 tok/s, Tight fit
5.4 GB required6.0 GB available
90% VRAM used

Fit status

Tight fit

Decode

40.2 tok/s

TTFT

4821 ms

Safe context

23K

Memory

5.4 GB / 6.0 GB

Memory breakdown

Weights2.4 GB
KV Cache1.5 GB
Runtime0.9 GB
Headroom0.6 GB

See how fast it feels

See how fast it feelsPhi 4 Mini 4B on Intel Arc A380 6GB
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: 40.2 tok/s decode · 4.8s TTFT (warm) · 100 tok/s prefill

What limits this setup

The raw memory story may look fine, but the software ecosystem is still a constraint here.

Runtime ecosystem is narrower than CUDA

Intel GPUs can look attractive on memory per dollar, but local AI tooling, kernels, and model coverage are still broader and easier on CUDA today.

Best improvement path

Prefer CUDA if you want the path of least resistance

If your goal is maximum runtime coverage, easier troubleshooting, and better support for new local AI releases, CUDA is usually still the safer upgrade path.

Performance by workload

WorkloadGradeFitDecodeTTFTContext
ChatARuns well37.4 tok/s2827 ms23K
CodingATight fit37.4 tok/s5183 ms23K
Agentic CodingBVery compromised21.1 tok/s13366 ms23K
ReasoningATight fit37.4 tok/s6125 ms23K
RAGBVery compromised21.1 tok/s16707 ms23K

Quantization options

How Phi 4 Mini 4B (4B params) fits at each quantization level on Intel Arc A380 6GB (6.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
1.6 GB
LowA75
Q3_K_S
3
2.0 GB
LowA75
NVFP4
4

Get started

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

Run

ollama run phi4-mini

Your hardware

More models your Intel Arc A380 6GB can run

ModelParamsGradeDecodeCapabilities
👁 Alibaba
Qwen 2.5 VL 7B		7BB14.1 tok/s
👁 Alibaba
Qwen 2.5 7B		7BB14.1 tok/s

Frequently asked questions

See all results for Intel Arc A380 6GBSee all hardware for Phi 4 Mini 4B
2.2 GB
Medium
A75
Q4_K_M
4
2.4 GB
MediumA75
Q5_K_M
5
2.9 GB
HighA75
Q6_KBest for your GPU
6
3.3 GB
HighA74
Q8_0
8
4.3 GB
Very HighF0
F16
16
8.2 GB
MaximumF0
👁 Mistral AI
Codestral Mamba 7B
7B
A
16.8 tok/s
👁 Google
Gemma 4 E2B		5.1BA24.1 tok/s

Prefer CUDA if you want the path of least resistance. If your goal is maximum runtime coverage, easier troubleshooting, and better support for new local AI releases, CUDA is usually still the safer upgrade path.