Can I Run Command R Family on Framework Desktop (Ryzen AI Max+ 395, 128 GB)?
Newer alternative. Cohere has not released a newer model in this library. If you are choosing today, Mistral Small 4 is a comparable current option.
View Mistral Small 4 →
Written by Jakub Rusinowski · Last updated April 4, 2024
Yes — comfortably
Yes, comfortably — Command R+ (104B) at Q2_K needs about 37.1 GB of the 128 GB usable on Framework Desktop (Ryzen AI Max+ 395, 128 GB), leaving ~90.9 GB spare and running at ~5.4 tok/s (estimated), with room for about 65,536 tokens of context.
Confidence: high · Recommended quantization: Q2_K · Estimated speed: ~5.4 tok/s
Framework Desktop (Ryzen AI Max+ 395, 128 GB) — what it gives a model
| Usable memory for models | 128 GB |
| Memory bandwidth | 256 GB/s |
| Form factor | Mini PC |
| Operating system | Windows or Linux |
| Memory upgradeable | No — soldered |
Command R Family on Framework Desktop (Ryzen AI Max+ 395, 128 GB): memory by quantization
| Quant | Memory needed | Fits 128 GB? | Max context | Est. speed | Download |
|---|
| F16 | 210.9 GB | ✗ No | — | — | 208 GB |
| Q8_0 | 113.4 GB | ✓ Yes | 32K | ~1.7 tok/s | 110.5 GB |
| Q6_K | 88.2 GB | ✓ Yes | 64K | ~2.2 tok/s | 85.3 GB |
| Q5_K_M | 76.7 GB | ✓ Yes | 64K | ~2.6 tok/s | 73.7 GB |
| Q4_K_M | 65.7 GB | ✓ Yes | 64K | ~3 tok/s | 62.8 GB |
| Q3_K_M | 47.3 GB | ✓ Yes | 64K | ~4.2 tok/s | 44.3 GB |
| Q2_K | 37.1 GB | ✓ Yes | 64K | ~5.4 tok/s | 34.2 GB |
Which Command R Family sizes fit
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|
| Command R+ (104B) | 65.7 GB | ✓ Fits | ~3 tok/s |
| Command R (35B) | 32.7 GB | ✓ Fits | ~7.1 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.
- Memory on this machine is not upgradeable, so the configuration you buy is the ceiling for every model you will ever run on it.
Framework Desktop 128 GB limitations
- Memory is soldered LPDDR5X — unusually for Framework, this is the one component that cannot be upgraded.
- ROCm/Vulkan support for Strix Halo is younger than CUDA; check your runtime supports it before buying.
Recommended setup
Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving
How these numbers are calculated
- Memory need = quantized weights + KV cache at 8,192 tokens (f16) + 0.8 GB runtime overhead.
- 128 GB unified memory at 256 GB/s, shared between CPU and GPU.
- 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 Framework Desktop (Ryzen AI Max+ 395, 128 GB)?
Yes, comfortably — Command R+ (104B) at Q2_K needs about 37.1 GB of the 128 GB usable on Framework Desktop (Ryzen AI Max+ 395, 128 GB), leaving ~90.9 GB spare and running at ~5.4 tok/s (estimated), with room for about 65,536 tokens of context.
Which quantization of Command R Family should I use on Framework Desktop (Ryzen AI Max+ 395, 128 GB)?
Q2_K — it needs about 37.1 GB of the 128 GB available, downloads as roughly 34.2 GB, and runs at an estimated 5.4 tokens/sec with up to 64K of context.
What limits Command R Family on Framework Desktop (Ryzen AI Max+ 395, 128 GB)?
Nothing binding — the model fits with headroom and generates at a usable speed on this hardware.
Which runtime should I use?
Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving
Other Computers
Other Models on Framework Desktop (Ryzen AI Max+ 395, 128 GB)
Command R Family on GPUs
What This Model Is Good At
Model & Tools
← Can I Run It? | Command R Family model page | Check your hardware