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Can I run Seed-OSS 36B Instruct on 16GB RAM Laptop (CPU/iGPU only)?

Compatibility verdict VRAM threshold engine
No, not enough memory would not load

No. Seed-OSS 36B Instruct needs ~22.5 GB even at Q4_K_M, but 16GB RAM Laptop (CPU/iGPU only) only has ~12 GB usable.

Needs ~22.5 GB Device usable ~12 GB

Needs ~22.5 GB even at Q4_K_M, but only ~12 GB is usable.

That figure is at a 4k context and moves about ±15% as context length changes.

The gap is about 10.5 GB: Seed-OSS 36B Instruct needs roughly 22.5 GB at Q4_K_M and 16GB RAM Laptop (CPU/iGPU only) leaves only about 12 GB usable for a model. The lightest tracked hardware that runs Seed-OSS 36B Instruct is the Nvidia GeForce RTX 4090 (24GB) at 24 GB. See Seed-OSS 36B Instruct on Nvidia GeForce RTX 4090 (24GB).

Q4_K_M needed
~22.5 GB
Usable on device
~12 GB
Device memory
16 GB
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Which quant fits

Quant ladder vs ~12 GB usable
Q2_K
~17.3 GB
Q3_K_M
~19.8 GB
Q4_K_M
~22.5 GB
Q5_K_M
~27.9 GB
Q6_K
~31.7 GB
Q8_0
~38 GB
FP16
~74.5 GB
The line marks 16GB RAM Laptop (CPU/iGPU only)'s ~12 GB budget; rungs past it are too large.

How to run it

On Windows use LM Studio (Best GUI on Windows, auto-detects CUDA/Vulkan backends.).

Model Seed-OSS
Parameters
36B
Q4_K_M size
20.27 GB
Q8_0 size
35.78 GB
Context
512k
Full Seed-OSS 36B Instruct requirements →
Device Windows
Memory
16 GB ram
Usable for weights
~12 GB
Power draw
~28 W
Best runtime
Ollama (llama.cpp backend)
Best models for 16GB RAM Laptop (CPU/iGPU only) →

What you can run instead

Run Seed-OSS 36B Instruct on other hardware

FAQ

Can 16GB RAM Laptop (CPU/iGPU only) run Seed-OSS 36B Instruct?

No. Seed-OSS 36B Instruct needs ~22.5 GB even at Q4_K_M, but 16GB RAM Laptop (CPU/iGPU only) only has ~12 GB usable.

How much memory does Seed-OSS 36B Instruct need?

16GB RAM Laptop (CPU/iGPU only) does not have enough memory. At Q4_K_M the weights are ~20.27 GB; with KV cache and runtime overhead, budget ~22.5 GB at a 4k context.

What is the best tool to run Seed-OSS 36B Instruct 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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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.