Can I Run Phi-4 Family on 192 GB system RAM?
Written by Jakub Rusinowski · Last updated January 6, 2025
Yes — comfortably
Yes, comfortably — Phi-4 (14B) at Q6_K needs about 14 GB of the 153.6 GB usable on 192 GB system RAM, leaving ~139.6 GB spare and running at ~5.4 tok/s (estimated), with room for about 16,384 tokens of context.
Confidence: high · Recommended quantization: Q6_K · Estimated speed: ~5.4 tok/s
192 GB system RAM — what it gives a model
| Usable memory for models | 153.6 GB |
| Memory bandwidth | 90 GB/s |
Phi-4 Family on 192 GB system RAM: memory by quantization
| Quant | Memory needed | Fits 153.6 GB? | Max context | Est. speed | Download |
|---|
| F16 | 30.5 GB | ✓ Yes | 16K | ~2.3 tok/s | 28 GB |
| Q8_0 | 17.4 GB | ✓ Yes | 16K | ~4.2 tok/s | 14.9 GB |
| Q6_K | 14 GB | ✓ Yes | 16K | ~5.4 tok/s | 11.5 GB |
| Q5_K_M | 12.4 GB | ✓ Yes | 16K | ~6.2 tok/s | 9.9 GB |
| Q4_K_M | 10.9 GB | ✓ Yes | 16K | ~7.1 tok/s | 8.5 GB |
| Q3_K_M | 8.4 GB | ✓ Yes | 16K | ~9.7 tok/s | 6 GB |
| Q2_K | 7.1 GB | ✓ Yes | 16K | ~12 tok/s | 4.6 GB |
What to watch out for
- These figures assume CPU-only inference. Any discrete GPU, even an 8 GB one, will be several times faster for models that fit in its VRAM.
Recommended setup
llama.cpp (CPU build) or Ollama — both run without a GPU
How these numbers are calculated
- Memory need = quantized weights + KV cache at 8,192 tokens (f16) + 0.8 GB runtime overhead.
- 153.6 GB of the 192 GB is treated as usable for model weights (80% — the rest is the OS and running applications).
- DDR5-5600 dual channel at 89.6 GB/s peak. CPU decode is assumed to sustain 35% of that peak, because CPU inference is not purely bandwidth-bound — it also spends real time in compute and thread synchronisation. This figure is an assumption, not a fitted constant: no CPU measurement is in the calibration set.
- CPU-only inference: no GPU is assumed. A GPU of any size will beat these figures substantially.
- Throughput is a memory-bandwidth roofline estimate, not a measurement. It is labelled "estimated" everywhere it appears.
- KV cache is computed from this model's published attention configuration.
FAQ
Can I run Phi-4 Family on 192 GB system RAM?
Yes, comfortably — Phi-4 (14B) at Q6_K needs about 14 GB of the 153.6 GB usable on 192 GB system RAM, leaving ~139.6 GB spare and running at ~5.4 tok/s (estimated), with room for about 16,384 tokens of context.
Which quantization of Phi-4 Family should I use on 192 GB system RAM?
Q6_K — it needs about 14 GB of the 153.6 GB available, downloads as roughly 11.5 GB, and runs at an estimated 5.4 tokens/sec with up to 16K of context.
What limits Phi-4 Family on 192 GB system RAM?
Nothing binding — the model fits with headroom and generates at a usable speed on this hardware.
Which runtime should I use?
llama.cpp (CPU build) or Ollama — both run without a GPU
Other RAM Capacities
Other Models on 192 GB system RAM
Phi-4 Family on GPUs
What This Model Is Good At
Model & Tools
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