Can I Run Llama 4 on 96 GB system RAM?
Written by Jakub Rusinowski · Last updated April 5, 2025
Yes
Yes — Llama 4 Scout 17B at Q4_K_M needs about 68.2 GB of the 76.8 GB usable on 96 GB system RAM (~8.6 GB spare), at ~6 tok/s (estimated), with room for about 32,768 tokens of context.
Confidence: high · Recommended quantization: Q4_K_M · Estimated speed: ~6 tok/s
96 GB system RAM — what it gives a model
| Usable memory for models | 76.8 GB |
| Memory bandwidth | 90 GB/s |
Llama 4 on 96 GB system RAM: memory by quantization
| Quant | Memory needed | Fits 76.8 GB? | Max context | Est. speed | Download |
|---|
| F16 | 220.4 GB | ✗ No | — | — | 218 GB |
| Q8_0 | 118.2 GB | ✗ No | — | — | 115.8 GB |
| Q6_K | 91.8 GB | ✗ No | — | — | 89.4 GB |
| Q5_K_M | 79.7 GB | ✗ No | — | — | 77.3 GB |
| Q4_K_M | 68.2 GB | ✓ Yes | 32K | ~6 tok/s | 65.8 GB |
| Q3_K_M | 48.9 GB | ✓ Yes | 128K | ~8.2 tok/s | 46.5 GB |
| Q2_K | 38.2 GB | ✓ Yes | 128K | ~10.3 tok/s | 35.8 GB |
Which Llama 4 sizes fit
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|
| Llama 4 Maverick 17B | 243.9 GB | ✗ Too large | — |
| Llama 4 Scout 17B | 68.2 GB | ✓ Fits | ~6 tok/s |
What to watch out for
- 1 larger variant of Llama 4 does not fit and would need CPU offload or different hardware.
- 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.
- 76.8 GB of the 96 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 Llama 4 on 96 GB system RAM?
Yes — Llama 4 Scout 17B at Q4_K_M needs about 68.2 GB of the 76.8 GB usable on 96 GB system RAM (~8.6 GB spare), at ~6 tok/s (estimated), with room for about 32,768 tokens of context.
Which quantization of Llama 4 should I use on 96 GB system RAM?
Q4_K_M — it needs about 68.2 GB of the 76.8 GB available, downloads as roughly 65.8 GB, and runs at an estimated 6 tokens/sec with up to 32K of context.
What limits Llama 4 on 96 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 96 GB system RAM
Llama 4 on GPUs
What This Model Is Good At
Model & Tools
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