Can I Run Cosmos 3 on 64 GB system RAM?
Written by Jakub Rusinowski · Last updated July 21, 2026
Yes — comfortably
Yes, comfortably — Cosmos 3 Super at Q2_K needs about 24.2 GB of the 51.2 GB usable on 64 GB system RAM, leaving ~27 GB spare and running at ~5.7 tok/s (estimated), with room for about 16,384 tokens of context.
Confidence: medium · Recommended quantization: Q2_K · Estimated speed: ~5.7 tok/s
64 GB system RAM — what it gives a model
| Usable memory for models | 51.2 GB |
| Memory bandwidth | 90 GB/s |
Cosmos 3 on 64 GB system RAM: memory by quantization
| Quant | Memory needed | Fits 51.2 GB? | Max context | Est. speed | Download |
|---|
| F16 | 131.1 GB | ✗ No | — | — | 128 GB |
| Q8_0 | 71.1 GB | ✗ No | — | — | 68 GB |
| Q6_K | 55.6 GB | ✗ No | — | — | 52.5 GB |
| Q5_K_M | 48.5 GB | ✓ Yes | 16K | ~2.8 tok/s | 45.4 GB |
| Q4_K_M | 41.8 GB | ✓ Yes | 16K | ~3.3 tok/s | 38.6 GB |
| Q3_K_M | 30.4 GB | ✓ Yes | 16K | ~4.5 tok/s | 27.3 GB |
| Q2_K | 24.2 GB | ✓ Yes | 16K | ~5.7 tok/s | 21 GB |
Which Cosmos 3 sizes fit
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|
| Cosmos 3 Super | 41.8 GB | ✓ Fits | ~3.3 tok/s |
| Cosmos 3 Nano | 11.9 GB | ✓ Fits | ~11.8 tok/s |
| Cosmos 3 Edge | 4.1 GB | ✓ Fits | ~37.1 tok/s |
What to watch out for
- Q2_K is the only quantization that fits, and it is a heavily degraded one — expect noticeably worse output than the same model at Q4_K_M. A smaller model at Q4 is usually the better trade.
- This model does not publish its full attention configuration, so the KV-cache share of these figures is inferred from its parameter count rather than computed exactly.
- 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.
- 51.2 GB of the 64 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 inferred from the parameter count because this model does not publish its full attention configuration.
FAQ
Can I run Cosmos 3 on 64 GB system RAM?
Yes, comfortably — Cosmos 3 Super at Q2_K needs about 24.2 GB of the 51.2 GB usable on 64 GB system RAM, leaving ~27 GB spare and running at ~5.7 tok/s (estimated), with room for about 16,384 tokens of context.
Which quantization of Cosmos 3 should I use on 64 GB system RAM?
Q2_K — it needs about 24.2 GB of the 51.2 GB available, downloads as roughly 21 GB, and runs at an estimated 5.7 tokens/sec with up to 16K of context.
What limits Cosmos 3 on 64 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 64 GB system RAM
Cosmos 3 on GPUs
What This Model Is Good At
Model & Tools
← Can I Run It? | Cosmos 3 model page | Check your hardware