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Phi-4 14B needs 8.5 GB VRAM at Q4. The RTX 4080 Super 16GB has 16 GB.
Φ Phi-4 14B (Microsoft) is a 14B-parameter model for reasoning, math, structured tasks. Microsoft’s reasoning-focused model, punches above its size. The question is whether the RTX 4080 Super 16GB’s 16 GB of VRAM can hold it — here’s the exact math.
VRAM requirements
| Quantization | VRAM needed | RTX 4080 Super 16GB |
|---|---|---|
| Q4_K_M (recommended) | 8.5 GB | ✅ |
| Q8_0 (near-lossless) | 15 GB | ✅ |
Expected performance
Running Phi-4 14B at Q4 on the RTX 4080 Super 16GB, expect roughly ~46 tokens/sec in Ollama or llama.cpp — comfortably faster than reading speed, so chat feels responsive.
Headroom: 8.5 GB used of 16 GB leaves about 7.5 GB free for KV cache (context). That’s fine for 4-8K context; for 32K+ you may need a smaller batch or a lower quant.
About the RTX 4080 Super 16GB
Architecture: Ada · VRAM: 16 GB · Price: ~$1,000.
Good: Very fast inference, excellent for real-time 14-27B chat
Watch out: Still 16GB — 70B needs offloading or a 24GB+ card
Check current RTX 4080 Super 16GB price on Amazon →
Related checks
Other models on the RTX 4080 Super 16GB
🎯 LLM Hardware Checker
Enter your exact GPU + RAM, see every model you can run.
💾 VRAM Requirements
Exact VRAM per model at Q4/Q5/Q8/FP16 with context scaling.
Frequently asked questions
Can the RTX 4080 Super 16GB run Phi-4 14B?
Yes — runs at Q4 and full Q8 quality. Phi-4 14B needs 8.5 GB VRAM at Q4_K_M; the RTX 4080 Super 16GB has 16 GB.
How much VRAM does Phi-4 14B need?
Phi-4 14B needs about 8.5 GB at Q4_K_M (recommended) and 15 GB at Q8_0.
How many tokens per second will the RTX 4080 Super 16GB get on Phi-4 14B?
Roughly ~46 tokens/sec at Q4 in Ollama or llama.cpp.
About the speed figure. The tokens/sec number above is an estimate, not a measured benchmark. Real throughput depends on your runtime and backend (Ollama, llama.cpp, vLLM), the exact quantization you download, context length, memory bandwidth, and whether any layers are offloaded to CPU. Treat it as a rough guide to the tier of performance, not a promised result.