text model · Ornith · Windows

Can I run Ornith 1.0 9B on 16GB RAM Laptop (CPU/iGPU only)?

Compatibility verdict VRAM threshold engine

Yes, it runs slow on this hardware ~8 tok/s est.

Yes. Ornith 1.0 9B runs on 16GB RAM Laptop (CPU/iGPU only) at Q4_K_M (~7.1 GB of ~12 GB usable).

Needs ~7.1 GB Device usable ~12 GB

Runs at Q4_K_M using ~7.1 GB of ~12 GB usable. You have room for Q8_0 for higher quality.

That figure is at a 4k context and moves about ±15% as context length changes. 16GB RAM Laptop (CPU/iGPU only) leaves ~4.9 GB of headroom, room to step up to Q8_0 for higher quality.

Q4_K_M needed: ~7.1 GB
Usable on device: ~12 GB
Device memory: 16 GB
Best quant: Q4_K_M

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Which quant fits

Quant ladder vs ~12 GB usable

Q2_K

~5.3 GB

Q3_K_M

~5.9 GB

Q4_K_M

~7.1 GB

Q5_K_M

~7.9 GB

Q6_K

~8.9 GB

Q8_0

~11 GB

FP16

~19.5 GB

The line marks 16GB RAM Laptop (CPU/iGPU only)'s ~12 GB budget; rungs past it are too large.

Running cost · estimate

Power & economics est.

Power draw: ~28 W
Electricity / 1M tokens: ~$0.15
Pays for itself after: ~2,143M tok

At ~$0.15/kWh and the estimated ~8 tok/s, a million generated tokens costs about $0.15 in electricity. Versus a hosted API at ~$0.5 per million tokens, the ~$750 16GB RAM Laptop (CPU/iGPU only) pays for itself after roughly 2,143 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 ornith:9b

llama.cpp

$ llama-cli -hf deepreinforce-ai/Ornith-1.0-9B-GGUF:Q4_K_M

LM Studio

$ lms get deepreinforce-ai/Ornith-1.0-9B-GGUF

Model Ornith

Parameters: 9B
Q4_K_M size: 5.6 GB
Q8_0 size: 9.5 GB
Context: 256k
Ollama tag: ornith:9b

Full Ornith 1.0 9B 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) →

You could also run

Run Ornith 1.0 9B on other hardware

Nvidia GeForce RTX 3060 (12GB)Nvidia GeForce RTX 4070 (12GB)Samsung Galaxy S24 Ultra Generic Android Phone (12GB RAM)iPhone 17 Pro iPhone Air

FAQ

Can 16GB RAM Laptop (CPU/iGPU only) run Ornith 1.0 9B?

Yes. Ornith 1.0 9B runs on 16GB RAM Laptop (CPU/iGPU only) at Q4_K_M (~7.1 GB of ~12 GB usable).

How much memory does Ornith 1.0 9B need?

16GB RAM Laptop (CPU/iGPU only) has room to spare. At Q4_K_M the weights are ~5.6 GB; with KV cache and runtime overhead, budget ~7.1 GB at a 4k context.

What is the best tool to run Ornith 1.0 9B 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

[![Ornith 1.0 9B on 16GB RAM Laptop (CPU/iGPU only)](https://localmodel.run/badge/ornith-1.0-9b/laptop-16gb.svg)](https://localmodel.run/can-i-run/ornith-1.0-9b/laptop-16gb)

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.