Can I Run Command R Family on 48 GB system RAM?
作者： Jakub Rusinowski · 最后更新： 2024年4月4日
Technically yes, but not recommended
It loads, but it is not worth running — Command R (35B) at Q5_K_M fits in 48 GB system RAM's 38.4 GB, yet the memory bandwidth limits it to ~2.2 tok/s (estimated), well below usable interactive speed.
Confidence: high · Recommended quantization: Q5_K_M · Estimated speed: ~2.2 tok/s
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48 GB system RAM — what it gives a model
| Usable memory for models | 38.4 GB |
| Memory bandwidth | 90 GB/s |
Command R Family on 48 GB system RAM: memory by quantization
| Quant | Memory needed | Fits 38.4 GB? | Max context | Est. speed | Download |
|---|---|---|---|---|---|
| F16 | 81.5 GB | ✗ No | — | — | 70 GB |
| Q8_0 | 48.7 GB | ✗ No | — | — | 37.2 GB |
| Q6_K | 40.2 GB | ✗ No | — | — | 28.7 GB |
| Q5_K_M | 36.3 GB | ✓ Yes | 8K | ~2.2 tok/s | 24.8 GB |
| Q4_K_M | 32.7 GB | ✓ Yes | 8K | ~2.5 tok/s | 21.1 GB |
| Q3_K_M | 26.5 GB | ✓ Yes | 16K | ~3.3 tok/s | 14.9 GB |
| Q2_K | 23 GB | ✓ Yes | 16K | ~3.9 tok/s | 11.5 GB |
Which Command R Family sizes fit
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|---|---|---|
| Command R+ (104B) | 65.7 GB | ✗ Too large | — |
| Command R (35B) | 32.7 GB | ✓ Fits | ~2.5 tok/s |
What to watch out for
- At ~2.2 tok/s this loads but is too slow for interactive use — expect roughly 27 seconds per 60 tokens.
- 1 larger variant of Command R Family 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.
- 38.4 GB of the 48 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 Command R Family on 48 GB system RAM?
It loads, but it is not worth running — Command R (35B) at Q5_K_M fits in 48 GB system RAM's 38.4 GB, yet the memory bandwidth limits it to ~2.2 tok/s (estimated), well below usable interactive speed.
Which quantization of Command R Family should I use on 48 GB system RAM?
Q5_K_M — it needs about 36.3 GB of the 38.4 GB available, downloads as roughly 24.8 GB, and runs at an estimated 2.2 tokens/sec with up to 8K of context.
What limits Command R Family on 48 GB system RAM?
Memory bandwidth. The model fits, but at 89.6 GB/s it can only be read fast enough for roughly 2.2 tokens/sec.
Which runtime should I use?
llama.cpp (CPU build) or Ollama — both run without a GPU
Other RAM Capacities
Other Models on 48 GB system RAM
- Cosmos 3 on 48 GB system RAM
- DeepSeek-OCR on 48 GB system RAM
- DeepSeek R1 on 48 GB system RAM
- Devstral on 48 GB system RAM
- EXAONE 3.5 on 48 GB system RAM
Command R Family on GPUs
- Command R Family on NVIDIA GeForce RTX 5090
- Command R Family on NVIDIA GeForce RTX 5080
- Command R Family on NVIDIA GeForce RTX 5070 Ti
- Command R Family on NVIDIA GeForce RTX 5070
What This Model Is Good At
Model & Tools
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