Phi-4-reasoning-plus 14B needs ~17.2 GB VRAM. NVIDIA A100 40GB has 40.0 GB. With Q4_K_M quantization, expect ~146 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
156.6 tok/s
TTFT
1236 ms
Safe context
33K
Memory
17.2 GB / 40.0 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 | S | Runs well | 145.7 tok/s | 725 ms | 33K |
| Coding | S | Runs well | 145.7 tok/s | 1329 ms | 33K |
| Agentic Coding | S | Runs well | 145.7 tok/s | 1933 ms | 33K |
| Reasoning | S | Runs well | 145.7 tok/s | 1571 ms | 33K |
| RAG | S | Runs well | 145.7 tok/s | 2416 ms | 33K |
How Phi-4-reasoning-plus 14B (14.699999809265137B params) fits at each quantization level on NVIDIA A100 40GB (40.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.7 GB | Low | A82 |
Q3_K_S | 3 | 7.2 GB | Low | A83 |
NVFP4 | 4 |
Copy-paste commands to run Phi-4-reasoning-plus 14B on your machine.
Run
ollama run phi4-reasoningYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 30.5B | S | 197.5 tok/s | ||
| 27B | S | 85.7 tok/s |
Yes, NVIDIA A100 40GB can run Phi-4-reasoning-plus 14B with a S grade (Runs well). Expected decode speed: 145.7 tok/s.
Phi-4-reasoning-plus 14B (14.699999809265137B parameters) requires approximately 17.2 GB of memory with Q4_K_M quantization.
The recommended quantization for Phi-4-reasoning-plus 14B is Q4_K_M, which balances quality and memory efficiency.
On NVIDIA A100 40GB, Phi-4-reasoning-plus 14B achieves approximately 145.7 tokens per second decode speed with a time-to-first-token of 1329ms using Q4_K_M quantization.
For coding workloads, Phi-4-reasoning-plus 14B on NVIDIA A100 40GB receives a S grade with 145.7 tok/s and 33K context.
On NVIDIA A100 40GB, Phi-4-reasoning-plus 14B can safely use up to 33K tokens of context. The model's official context limit is 33K, 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/phi-4-reasoning-plus-14b-on-a100-40gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
8.2 GB |
| Medium |
| A83 |
Q4_K_M | 4 | 9.0 GB | Medium | A83 |
Q5_K_M | 5 | 10.6 GB | High | A84 |
Q6_K | 6 | 12.1 GB | High | A84 |
Q8_0 | 8 | 15.7 GB | Very High | S86 |
F16Best for your GPU | 16 | 30.1 GB | Maximum | S88 |
| 27B | S | 85.9 tok/s |
| 35B | S | 166 tok/s |
| 30B | S | 204.3 tok/s |