text model · Kimi · Windows
Can I run Kimi K2.6 on 32GB RAM Laptop (CPU/iGPU only)?
No. Kimi K2.6 needs ~592.1 GB even at Q4_K_M, but 32GB RAM Laptop (CPU/iGPU only) only has ~28 GB usable.
Needs ~592.1 GB even at Q4_K_M, but only ~28 GB is usable.
That figure is at a 4k context and moves about ±15% as context length changes.
The gap is about 564.1 GB: Kimi K2.6 needs roughly 592.1 GB at Q4_K_M and 32GB RAM Laptop (CPU/iGPU only) leaves only about 28 GB usable for a model. No single tracked device has enough memory; Kimi K2.6 needs a multi-GPU or high-memory rig.
- Q4_K_M needed
- ~592.1 GB
- Usable on device
- ~28 GB
- Device memory
- 32 GB
Which quant fits
How to run it
On Windows use LM Studio (Best GUI on Windows, auto-detects CUDA/Vulkan backends.).
- Parameters
- 1000B (MoE, 32B active)
- Q4_K_M size
- 583.71 GB
- Context
- 256k
- Memory
- 32 GB ram
- Usable for weights
- ~28 GB
- Power draw
- ~28 W
- Best runtime
- Ollama (llama.cpp backend)
What you can run instead
FAQ
Can 32GB RAM Laptop (CPU/iGPU only) run Kimi K2.6?
No. Kimi K2.6 needs ~592.1 GB even at Q4_K_M, but 32GB RAM Laptop (CPU/iGPU only) only has ~28 GB usable.
How much memory does Kimi K2.6 need?
32GB RAM Laptop (CPU/iGPU only) does not have enough memory. At Q4_K_M the weights are ~583.71 GB; with KV cache and runtime overhead, budget ~592.1 GB at a 4k context. It is a Mixture-of-Experts model (1000B total / 32B active), so all experts must stay in memory; memory tracks total params, not active params.
What is the best tool to run Kimi K2.6 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/kimi-k2.6/laptop-32gb) 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.