Intel Arc Pro B60 24GBGünstige Wahl24 GB VRAM (+8)
B
Adds memory headroom for longer context windows and future model growth.31 tok/s Dekodierung
Adds memory headroom for longer context windows and future model growth.
ca. $599 MSRP
Can Phi 3 Medium 14B run on Intel Arc A770 16GB?
YES — Tight Fit
B61Good
Estimated from fit model
Phi 3 Medium 14B needs ~14.1 GB VRAM. Intel Arc A770 16GB has 16.0 GB. With Q4_K_M quantization, expect ~30 tok/s.
Runtime: llama.cppCapacity: TightBandwidth: MediumStack: StandardBottleneck: Balanced
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.
Select quantization to explore
Q4_K_M (Medium quality) — 14.1 GB, 31.7 tok/s, Tight fit
14.1 GB required16.0 GB available
88% VRAM used
Fit status
Tight fit
Decode
31.7 tok/s
TTFT
6103 ms
Safe context
26K
Memory
14.1 GB / 16.0 GB
Memory breakdown
Weights8.5 GB
KV Cache3.1 GB
Runtime0.9 GB
Headroom1.6 GB
See how fast it feels
See how fast it feelsPhi 3 Medium 14B on Intel Arc A770 16GB
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: 31.7 tok/s decode · 6.1s TTFT (warm) · 79 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
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | B | Runs well | 31.7 tok/s | 3329 ms | 26K |
| Coding | B | Tight fit | 29.5 tok/s | 6561 ms | 26K |
| Agentic Coding | C | Runs with offload (needs ~0.6 GB host RAM) | 20.6 tok/s | 13688 ms | 26K |
| Reasoning | B | Tight fit | 31.7 tok/s | 7213 ms | 26K |
| RAG | C | Runs with offload (needs ~0.6 GB host RAM) | 20.6 tok/s | 17110 ms | 26K |
Quantization options
How Phi 3 Medium 14B (14B params) fits at each quantization level on Intel Arc A770 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.5 GB | Low | B60 |
Q3_K_S | 3 | 6.9 GB | Low | B62 |
NVFP4 | 4 | 7.8 GB | Medium | B63 |
Q4_K_M | 4 | 8.5 GB | Medium | B62 |
Q5_K_M | 5 | 10.1 GB | High | B62 |
Q6_KBest for your GPU | 6 | 11.5 GB | High | B62 |
Q8_0 | 8 | 15.0 GB | Very High | F0 |
F16 | 16 | 28.7 GB | Maximum | F0 |
Get started
Copy-paste commands to run Phi 3 Medium 14B on your machine.
Run
ollama run phi3:mediumUpgrade-Optionen
Hardware, die Phi 3 Medium 14B gut ausführt
Intel Arc Pro B60 24GBGünstige WahlRX 7900 XT 20GBBestes Preis-Leistungs-Verhältnis
20 GB VRAM (+4)800 GB/s (+240)
B
Raises estimated decode speed by about 91%.60.4 tok/s Dekodierung
Raises estimated decode speed by about 91%.
Adds memory headroom for longer context windows and future model growth.
ca. $899 MSRP
Frequently asked questions
Can Intel Arc A770 16GB run Phi 3 Medium 14B?
Yes, Intel Arc A770 16GB can run Phi 3 Medium 14B with a B grade (Tight fit). Expected decode speed: 29.5 tok/s.
How much VRAM does Phi 3 Medium 14B need?
Phi 3 Medium 14B (14B parameters) requires approximately 14.1 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 Intel Arc A770 16GB?
On Intel Arc A770 16GB, Phi 3 Medium 14B achieves approximately 29.5 tokens per second decode speed with a time-to-first-token of 6561ms using Q4_K_M quantization.
Can Intel Arc A770 16GB run Phi 3 Medium 14B for coding?
For coding workloads, Phi 3 Medium 14B on Intel Arc A770 16GB receives a B grade with 29.5 tok/s and 26K context.
What context window can Phi 3 Medium 14B use on Intel Arc A770 16GB?
On Intel Arc A770 16GB, Phi 3 Medium 14B can safely use up to 26K tokens of context. The model's official context limit is 128K, but available memory constrains the safe maximum.
What should I upgrade first if Phi 3 Medium 14B feels slow on Intel Arc A770 16GB?
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.
Would CUDA be a better path than Intel Arc A770 16GB for Phi 3 Medium 14B?
Often yes, if your goal is the easiest setup and the widest runtime support. Intel can offer attractive memory capacity, but CUDA still tends to win on tooling maturity, guides, kernels, and model coverage for local AI.
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