Phi 4 reasoning vision 15B needs ~18.5 GB VRAM. NVIDIA A16 64GB has 64.0 GB. With Q4_K_M quantization, expect ~51 tok/s.
Operating mode
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
Fit status
Runs well
Decode
51.1 tok/s
TTFT
3785 ms
Safe context
430K
Memory
18.5 GB / 64.0 GB
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.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | C | Runs well | 51.1 tok/s | 2065 ms | 430K |
| Coding | C | Runs well | 51.1 tok/s | 3785 ms | 430K |
| Agentic Coding | C | Runs well | 51.1 tok/s | 5506 ms | 430K |
| Reasoning | C | Runs well | 51.1 tok/s | 4473 ms | 430K |
| RAG | C | Runs well | 51.1 tok/s | 6882 ms | 430K |
How Phi 4 reasoning vision 15B (15B params) fits at each quantization level on NVIDIA A16 64GB (64.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.9 GB | Low | C41 |
Q3_K_S | 3 | 7.4 GB | Low | C41 |
NVFP4 | 4 | 8.4 GB | Medium | C41 |
Q4_K_M | 4 | 9.2 GB | Medium | C41 |
Q5_K_M | 5 | 10.8 GB | High | C41 |
Q6_K | 6 | 12.3 GB | High | C42 |
Q8_0 | 8 | 16.1 GB | Very High | C42 |
F16Best for your GPU | 16 | 30.7 GB | Maximum | C46 |
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
RTX PRO 6000 Blackwell Workstation Edition 96GB经济之选Raises estimated decode speed by about 222%.
Adds memory headroom for longer context windows and future model growth.
~$9,999 MSRP
RTX PRO 6000 Blackwell Server Edition 96GB最佳性价比Raises estimated decode speed by about 187%.
Adds memory headroom for longer context windows and future model growth.
~$9,999 MSRP
NVIDIA H20 96GBNVIDIA 升级Raises estimated decode speed by about 311%.
Adds memory headroom for longer context windows and future model growth.
~$12,000 MSRP
Yes, NVIDIA A16 64GB can run Phi 4 reasoning vision 15B with a C grade (Runs well). Expected decode speed: 51.1 tok/s.
Phi 4 reasoning vision 15B (15B parameters) requires approximately 18.5 GB of memory with Q4_K_M quantization.
The recommended quantization for Phi 4 reasoning vision 15B is Q4_K_M, which balances quality and memory efficiency.
On NVIDIA A16 64GB, Phi 4 reasoning vision 15B achieves approximately 51.1 tokens per second decode speed with a time-to-first-token of 3785ms using Q4_K_M quantization.
For coding workloads, Phi 4 reasoning vision 15B on NVIDIA A16 64GB receives a C grade with 51.1 tok/s and 430K context.
On NVIDIA A16 64GB, Phi 4 reasoning vision 15B can safely use up to 430K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/hf-jamesburton--phi-4-reasoning-vision-15b-gguf-on-a16-64gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
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