Phi-4-reasoning-plus 14B needs ~14.5 GB VRAM. Radeon RX 7900M 16GB has 16.0 GB. With Q4_K_M quantization, expect ~41 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
Tight fit
Decode
40.7 tok/s
TTFT
4752 ms
Safe context
24K
Memory
14.5 GB / 16.0 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 | 40.7 tok/s | 2592 ms | 24K |
| Coding | S | Tight fit | 40.7 tok/s | 4752 ms | 24K |
| Agentic Coding | A | Very compromised (needs ~0.8 GB host RAM) | 25.1 tok/s | 11224 ms | 24K |
| Reasoning | S | Tight fit | 40.7 tok/s | 5616 ms | 24K |
| RAG | A | Very compromised (needs ~0.8 GB host RAM) | 25.1 tok/s | 14030 ms | 24K |
How Phi-4-reasoning-plus 14B (14.699999809265137B params) fits at each quantization level on Radeon RX 7900M 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.7 GB | Low | S89 |
Q3_K_S | 3 | 7.2 GB | Low | S91 |
NVFP4 | 4 | 8.2 GB | Medium | S91 |
Q4_K_M | 4 | 9.0 GB | Medium | S91 |
Q5_K_M | 5 | 10.6 GB | High | S91 |
Q6_KBest for your GPU | 6 | 12.1 GB | High | S90 |
Q8_0 | 8 | 15.7 GB | Very High | F0 |
F16 | 16 | 30.1 GB | Maximum | F0 |
Copy-paste commands to run Phi-4-reasoning-plus 14B on your machine.
Run
ollama run phi4-reasoningYes, Radeon RX 7900M 16GB can run Phi-4-reasoning-plus 14B with a S grade (Tight fit). Expected decode speed: 40.7 tok/s.
Phi-4-reasoning-plus 14B (14.699999809265137B parameters) requires approximately 14.5 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 Radeon RX 7900M 16GB, Phi-4-reasoning-plus 14B achieves approximately 40.7 tokens per second decode speed with a time-to-first-token of 4752ms using Q4_K_M quantization.
For coding workloads, Phi-4-reasoning-plus 14B on Radeon RX 7900M 16GB receives a S grade with 40.7 tok/s and 24K context.
On Radeon RX 7900M 16GB, Phi-4-reasoning-plus 14B can safely use up to 24K 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-rx-7900m-16gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: