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text model · Seed-OSS · Windows

Can I run Seed-OSS 36B Instruct on 32GB RAM Laptop (CPU/iGPU only)?

Compatibility verdict VRAM threshold engine
Yes, it runs slow on this hardware ~2 tok/s est.

Yes. Seed-OSS 36B Instruct runs on 32GB RAM Laptop (CPU/iGPU only) at Q4_K_M (~22.5 GB of ~28 GB usable).

Needs ~22.5 GB Device usable ~28 GB

Runs at Q4_K_M using ~22.5 GB of ~28 GB usable.

That figure is at a 4k context and moves about ±15% as context length changes. 32GB RAM Laptop (CPU/iGPU only) leaves ~5.5 GB of headroom.

Q4_K_M needed
~22.5 GB
Usable on device
~28 GB
Device memory
32 GB
Best quant
Q4_K_M
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Which quant fits

Quant ladder vs ~28 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 32GB RAM Laptop (CPU/iGPU only)'s ~28 GB budget; rungs past it are too large.

Running cost · estimate

Power & economics est.
Power draw
~28 W
Electricity / 1M tokens
~$0.58

At ~$0.15/kWh and the estimated ~2 tok/s, a million generated tokens costs about $0.58 in electricity. TDP is the peak draw, so this is an upper bound. Assumptions.

Run it

Install commands Windows

Pick your tool. All 2 load the same Q4_K_M weights.

llama.cpp
$ llama-cli -hf bartowski/ByteDance-Seed_Seed-OSS-36B-Instruct-GGUF:Q4_K_M
LM Studio
$ lms get bartowski/ByteDance-Seed_Seed-OSS-36B-Instruct-GGUF

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
32 GB ram
Usable for weights
~28 GB
Power draw
~28 W
Best runtime
Ollama (llama.cpp backend)
Best models for 32GB RAM Laptop (CPU/iGPU only) →

You could also run

Run Seed-OSS 36B Instruct on other hardware

FAQ

Can 32GB RAM Laptop (CPU/iGPU only) run Seed-OSS 36B Instruct?

Yes. Seed-OSS 36B Instruct runs on 32GB RAM Laptop (CPU/iGPU only) at Q4_K_M (~22.5 GB of ~28 GB usable).

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

32GB RAM Laptop (CPU/iGPU only) has room to spare. 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.