text model · Ornith · Android
Can I run Ornith 1.0 9B on Samsung Galaxy S24 Ultra?
Yes. Ornith 1.0 9B runs on Samsung Galaxy S24 Ultra at Q4_K_M (~7.1 GB of ~8.5 GB usable).
Runs at Q4_K_M using ~7.1 GB of ~8.5 GB usable.
That figure is at a 4k context and moves about ±15% as context length changes. Samsung Galaxy S24 Ultra leaves ~1.4 GB of headroom.
- Q4_K_M needed
- ~7.1 GB
- Usable on device
- ~8.5 GB
- Device memory
- 12 GB
- Best quant
- Q4_K_M
Which quant fits
Running cost · estimate
- Power draw
- ~8 W
- Electricity / 1M tokens
- ~$0.05
- Pays for itself after
- ~2,887M tok
At ~$0.15/kWh and the estimated ~7 tok/s, a million generated tokens costs about $0.05 in electricity. Versus a hosted API at ~$0.5 per million tokens, the ~$1,299 Samsung Galaxy S24 Ultra pays for itself after roughly 2,887 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.
How to run it
On Android use PocketPal AI (Polished app, download GGUF and run offline.).
- Parameters
- 9B
- Q4_K_M size
- 5.6 GB
- Q8_0 size
- 9.5 GB
- Context
- 256k
- Ollama tag
- ornith:9b
- Memory
- 12 GB ram
- Usable for weights
- ~8.5 GB
- Power draw
- ~8 W
- Best runtime
- llama.cpp (PocketPal) or MLC-LLM (Adreno GPU path)
You could also run
Run Ornith 1.0 9B on other hardware
FAQ
Can Samsung Galaxy S24 Ultra run Ornith 1.0 9B?
Yes. Ornith 1.0 9B runs on Samsung Galaxy S24 Ultra at Q4_K_M (~7.1 GB of ~8.5 GB usable).
How much memory does Ornith 1.0 9B need?
Samsung Galaxy S24 Ultra 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 Android?
On Android, PocketPal AI (Polished app, download GGUF and run offline.) is the go-to option. NPU acceleration is limited and chip-specific; most apps run on CPU. Expect 1B-4B class.
Embed this
A live badge for your model card or README, updated as the data is. [](https://localmodel.run/can-i-run/ornith-1.0-9b/samsung-s24-ultra) Sources
- androidauthority.com
- comparigon.com
- deep-reinforce.com
- github.com/a-ghorbani
- github.com/google-ai-edge
- github.com/mlc-ai
- github.com/shubham0204
- github.com/Vali-98
- gsmarena.com/samsung_galaxy_s24_ultra-12419.php
- gsmarena.com/samsung_galaxy_s24_ultra-12771.php
- gsmarena.com/samsung_galaxy_s24_ultra-review-2754p5.php
- huggingface.co/bartowski
- huggingface.co/deepreinforce-ai/Ornith-1.0-9B
- huggingface.co/deepreinforce-ai/Ornith-1.0-9B-GGUF
- layla-network.ai
- ollama.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.