text model · Mistral · Windows
Can I run Mistral Small 3 24B on 8GB RAM Laptop (CPU/iGPU only)?
No. Mistral Small 3 24B needs ~16.3 GB even at Q4_K_M, but 8GB RAM Laptop (CPU/iGPU only) only has ~5 GB usable.
Needs ~16.3 GB even at Q4_K_M, but only ~5 GB is usable.
That figure is at a 4k context and moves about ±15% as context length changes.
The gap is about 11.3 GB: Mistral Small 3 24B needs roughly 16.3 GB at Q4_K_M and 8GB RAM Laptop (CPU/iGPU only) leaves only about 5 GB usable for a model. The lightest tracked hardware that runs Mistral Small 3 24B is the Nvidia GeForce RTX 4090 (24GB) at 24 GB. See Mistral Small 3 24B on Nvidia GeForce RTX 4090 (24GB).
- Q4_K_M needed
- ~16.3 GB
- Usable on device
- ~5 GB
- Device memory
- 8 GB
Which quant fits
- Parameters
- 24B
- Q4_K_M size
- 14.33 GB
- Q8_0 size
- 25.05 GB
- Context
- 128k
- Ollama tag
- mistral-small3.2:24b
- Memory
- 8 GB ram
- Usable for weights
- ~5 GB
- Power draw
- ~15 W
- Best runtime
- Ollama (llama.cpp backend)
What you can run instead
Run Mistral Small 3 24B on other hardware
FAQ
Can 8GB RAM Laptop (CPU/iGPU only) run Mistral Small 3 24B?
No. Mistral Small 3 24B needs ~16.3 GB even at Q4_K_M, but 8GB RAM Laptop (CPU/iGPU only) only has ~5 GB usable.
How much memory does Mistral Small 3 24B need?
8GB RAM Laptop (CPU/iGPU only) does not have enough memory. At Q4_K_M the weights are ~14.33 GB; with KV cache and runtime overhead, budget ~16.3 GB at a 4k context.
What is the best tool to run Mistral Small 3 24B 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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A live badge for your model card or README, updated as the data is. [](https://localmodel.run/can-i-run/mistral-small-3-24b/laptop-8gb) Sources
- amazon.com
- docs.mistral.ai
- en.wikipedia.org
- huggingface.co/bartowski/Llama-3.2-1B-Instruct-GGUF
- huggingface.co/bartowski/mistralai_Mistral-Small-3.2-24B-Instruct-2506-GGUF
- lmarena.ai
- lmstudio.ai
- notebookcheck.net
- ollama.com
- ollama.com/library/llama3.2:1b
- ollama.com/library/mistral-small3.2
- ollama.com/library/mistral-small3.2/tags
- ollama.com/library/phi3:mini
- store.acer.com
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.