text model · Command · Windows
Can I run Command A on AMD Ryzen AI Halo (128GB)?
Yes. Command A runs on AMD Ryzen AI Halo (128GB) at Q4_K_M (~70.4 GB of ~96 GB usable).
Runs at Q4_K_M using ~70.4 GB of ~96 GB usable.
That figure is at a 4k context and moves about ±15% as context length changes. AMD Ryzen AI Halo (128GB) leaves ~25.6 GB of headroom.
- Q4_K_M needed
- ~70.4 GB
- Usable on device
- ~96 GB
- Device memory
- 128 GB
- Best quant
- Q4_K_M
Which quant fits
Running cost · estimate
- Power draw
- ~120 W
- Electricity / 1M tokens
- ~$2.5
At ~$0.15/kWh and the estimated ~2 tok/s, a million generated tokens costs about $2.5 in electricity. TDP is the peak draw, so this is an upper bound. Assumptions.
Run it
Pick your tool. All 3 load the same Q4_K_M weights.
ollama run command-a:111b llama-cli -hf lmstudio-community/c4ai-command-a-03-2025-GGUF:Q4_K_M lms get lmstudio-community/c4ai-command-a-03-2025-GGUF - Parameters
- 111B
- Q4_K_M size
- 67.1 GB
- Q8_0 size
- 118 GB
- Context
- 256k
- Ollama tag
- command-a:111b
- Memory
- 128 GB unified
- Usable for weights
- ~96 GB
- Power draw
- ~120 W
- Best runtime
- llama.cpp (Vulkan/ROCm) / LM Studio
You could also run
Run Command A on other hardware
FAQ
Can AMD Ryzen AI Halo (128GB) run Command A?
Yes. Command A runs on AMD Ryzen AI Halo (128GB) at Q4_K_M (~70.4 GB of ~96 GB usable).
How much memory does Command A need?
AMD Ryzen AI Halo (128GB) has room to spare. At Q4_K_M the weights are ~67.1 GB; with KV cache and runtime overhead, budget ~70.4 GB at a 4k context.
What is the best tool to run Command A on Windows?
LM Studio for a simple setup; Ollama (CUDA) for the most speed. AMD GPUs run via Vulkan/ROCm at roughly half CUDA throughput. NVIDIA is the smooth path on Windows.
Embed this
A live badge for your model card or README, updated as the data is. [](https://localmodel.run/can-i-run/command-a-111b/amd-ryzen-ai-halo-128gb) Sources
Weights are measured from GGUF files; KV cache and overhead are computed, so totals can vary ~15% with context and runtime. Any tok/s is a bandwidth estimate. See methodology.