20 GB VRAM (+4)
C
Adds memory headroom for longer context windows and future model growth.30.7 tok/s decode
Adds memory headroom for longer context windows and future model growth.
~$1,250 MSRP
Can Phi 4 reasoning vision 15B run on RTX 4080 Super 16GB?
YES — Tight Fit
C53Usable
○Estimated from fit model
Phi 4 reasoning vision 15B needs ~13.4 GB VRAM. RTX 4080 Super 16GB has 16.0 GB. With Q4_K_M quantization, expect ~68 tok/s.
Runtime: llama.cppCapacity: TightBandwidth: MediumStack: StandardBottleneck: Balanced
Share:
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) — 13.4 GB, 68.3 tok/s, Tight fit
13.4 GB required16.0 GB available
84% VRAM used
Fit status
Tight fit
Decode
68.3 tok/s
TTFT
2835 ms
Safe context
40K
Memory
13.4 GB / 16.0 GB
Memory breakdown
Weights9.2 GB
KV Cache1.8 GB
Runtime0.9 GB
Headroom1.6 GB
See how fast it feels
See how fast it feelsPhi 4 reasoning vision 15B on RTX 4080 Super 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: 68.3 tok/s decode · 2.8s TTFT (warm) · 171 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
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | B | Runs well | 68.3 tok/s | 1547 ms | 40K |
| Coding | C | Tight fit | 68.3 tok/s | 2835 ms | 40K |
| Agentic Coding | C | Tight fit | 68.3 tok/s | 4124 ms | 40K |
| Reasoning | C | Tight fit | 68.3 tok/s | 3351 ms | 40K |
| RAG | C | Tight fit | 68.3 tok/s | 5155 ms | 40K |
Quantization options
How Phi 4 reasoning vision 15B (15B params) fits at each quantization level on RTX 4080 Super 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.9 GB | Low | C50 |
Q3_K_S | 3 | 7.4 GB | Low | C51 |
NVFP4 | 4 | 8.4 GB | Medium | C51 |
Q4_K_M | 4 | 9.2 GB | Medium | C51 |
Q5_K_M | 5 | 10.8 GB | High | C51 |
Q6_KBest for your GPU | 6 | 12.3 GB | High | C50 |
Q8_0 | 8 | 16.1 GB | Very High | F0 |
F16 | 16 | 30.7 GB | Maximum | F0 |
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 startUpgrade options
Hardware that runs Phi 4 reasoning vision 15B well
24 GB VRAM (+8)936 GB/s (+200)
C
Adds memory headroom for longer context windows and future model growth.68.3 tok/s decode
Adds memory headroom for longer context windows and future model growth.
~$1,499 MSRP
24 GB VRAM (+8)1008 GB/s (+272)
C
Raises estimated decode speed by about 25%.85.6 tok/s decode
Raises estimated decode speed by about 25%.
Adds memory headroom for longer context windows and future model growth.
~$1,599 MSRP