text model · Mistral · Windows

Can I run Mistral Nemo 12B on AMD Ryzen AI Halo (128GB)?

Compatibility verdict VRAM threshold engine

Yes, it runs GPU accelerated ~24 tok/s est.

Yes. Mistral Nemo 12B runs on AMD Ryzen AI Halo (128GB) at Q4_K_M (~8.6 GB of ~96 GB usable).

Needs ~8.6 GB Device usable ~96 GB

Runs at Q4_K_M using ~8.6 GB of ~96 GB usable. You have room for FP16 for higher quality.

That figure is at a 4k context and moves about ±15% as context length changes. AMD Ryzen AI Halo (128GB) leaves ~87.4 GB of headroom, room to step up to FP16 for higher quality.

Q4_K_M needed: ~8.6 GB
Usable on device: ~96 GB
Device memory: 128 GB
Best quant: Q4_K_M

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Which quant fits

Quant ladder vs ~96 GB usable

Q2_K

~6.7 GB

Q3_K_M

~7.6 GB

Q4_K_M

~8.6 GB

Q5_K_M

~10.3 GB

Q6_K

~11.6 GB

Q8_0

~13.7 GB

FP16

~26 GB

The line marks AMD Ryzen AI Halo (128GB)'s ~96 GB budget; rungs past it are too large.

Running cost · estimate

Power & economics est.

Power draw: ~120 W
Electricity / 1M tokens: ~$0.21
Pays for itself after: ~13,790M tok

At ~$0.15/kWh and the estimated ~24 tok/s, a million generated tokens costs about $0.21 in electricity. Versus a hosted API at ~$0.5 per million tokens, the ~$3,999 AMD Ryzen AI Halo (128GB) pays for itself after roughly 13,790 million tokens, so local hardware is mostly a fixed cost, not a per-token one. TDP is the peak draw, so this is an upper bound. Assumptions.

Run it

Install commands Windows

Pick your tool. All 3 load the same Q4_K_M weights.

Ollama

$ ollama run mistral-nemo:12b

llama.cpp

$ llama-cli -hf bartowski/Mistral-Nemo-Instruct-2407-GGUF:Q4_K_M

LM Studio

$ lms get bartowski/Mistral-Nemo-Instruct-2407-GGUF

Model Mistral

Parameters: 12.2B
Q4_K_M size: 6.96 GB
Q8_0 size: 12.13 GB
Context: 128k
Ollama tag: mistral-nemo:12b

Full Mistral Nemo 12B requirements →

Device Windows

Memory: 128 GB unified
Usable for weights: ~96 GB
Power draw: ~120 W
Best runtime: llama.cpp (Vulkan/ROCm) / LM Studio

Best models for AMD Ryzen AI Halo (128GB) →

You could also run

Run Mistral Nemo 12B on other hardware

Nvidia GeForce RTX 3060 (12GB)Nvidia GeForce RTX 4070 (12GB)Apple M2 (16GB)Apple M4 (16GB)Nvidia GeForce RTX 4060 Ti (16GB)Nvidia GeForce RTX 4080 (16GB)

FAQ

Can AMD Ryzen AI Halo (128GB) run Mistral Nemo 12B?

Yes. Mistral Nemo 12B runs on AMD Ryzen AI Halo (128GB) at Q4_K_M (~8.6 GB of ~96 GB usable).

How much memory does Mistral Nemo 12B need?

AMD Ryzen AI Halo (128GB) has room to spare. At Q4_K_M the weights are ~6.96 GB; with KV cache and runtime overhead, budget ~8.6 GB at a 4k context.

What is the best tool to run Mistral Nemo 12B 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.

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Markdown

[![Mistral Nemo 12B on AMD Ryzen AI Halo (128GB)](https://localmodel.run/badge/mistral-nemo-12b/amd-ryzen-ai-halo-128gb.svg)](https://localmodel.run/can-i-run/mistral-nemo-12b/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.