text model · Olmo · Android
Can I run Olmo 3 7B Instruct on Generic Android Phone (12GB RAM)?
Yes. Olmo 3 7B Instruct runs on Generic Android Phone (12GB RAM) at Q4_K_M (~5.6 GB of ~8.5 GB usable).
Runs at Q4_K_M using ~5.6 GB of ~8.5 GB usable.
That figure is at a 4k context and moves about ±15% as context length changes. Generic Android Phone (12GB RAM) leaves ~2.9 GB of headroom.
- Q4_K_M needed
- ~5.6 GB
- Usable on device
- ~8.5 GB
- Device memory
- 12 GB
- Best quant
- Q4_K_M
Which quant fits
How to run it
On Android use PocketPal AI (Polished app, download GGUF and run offline.).
- Parameters
- 7B
- Q4_K_M size
- 4.16 GB
- Q8_0 size
- 7.23 GB
- Context
- 64k
- Ollama tag
- olmo-3:7b-instruct
- Memory
- 12 GB ram
- Usable for weights
- ~8.5 GB
- Best runtime
- llama.cpp (PocketPal) or MLC-LLM
You could also run
Run Olmo 3 7B Instruct on other hardware
FAQ
Can Generic Android Phone (12GB RAM) run Olmo 3 7B Instruct?
Yes. Olmo 3 7B Instruct runs on Generic Android Phone (12GB RAM) at Q4_K_M (~5.6 GB of ~8.5 GB usable).
How much memory does Olmo 3 7B Instruct need?
Generic Android Phone (12GB RAM) has room to spare. At Q4_K_M the weights are ~4.16 GB; with KV cache and runtime overhead, budget ~5.6 GB at a 4k context.
What is the best tool to run Olmo 3 7B Instruct 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.
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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.