text model · gpt-oss · Android
Can I run gpt-oss 120B on Generic Android Phone (12GB RAM)?
No. gpt-oss 120B needs ~62.4 GB even at Q4_K_M, but Generic Android Phone (12GB RAM) only has ~8.5 GB usable.
Needs ~62.4 GB even at Q4_K_M, but only ~8.5 GB is usable.
That figure is at a 4k context and moves about ±15% as context length changes.
The gap is about 53.9 GB: gpt-oss 120B needs roughly 62.4 GB at Q4_K_M and Generic Android Phone (12GB RAM) leaves only about 8.5 GB usable for a model. The lightest tracked hardware that runs gpt-oss 120B is the Apple M4 Max (128GB) at 128 GB. See gpt-oss 120B on Apple M4 Max (128GB).
- Q4_K_M needed
- ~62.4 GB
- Usable on device
- ~8.5 GB
- Device memory
- 12 GB
Which quant fits
How to run it
On Android use PocketPal AI (Polished app, download GGUF and run offline.).
- Parameters
- 117B (MoE, 5.1B active)
- Q4_K_M size
- 59.03 GB
- Q8_0 size
- 0.79 GB
- Context
- 128k
- Ollama tag
- gpt-oss:120b
- Memory
- 12 GB ram
- Usable for weights
- ~8.5 GB
- Best runtime
- llama.cpp (PocketPal) or MLC-LLM
What you can run instead
Run gpt-oss 120B on other hardware
FAQ
Can Generic Android Phone (12GB RAM) run gpt-oss 120B?
No. gpt-oss 120B needs ~62.4 GB even at Q4_K_M, but Generic Android Phone (12GB RAM) only has ~8.5 GB usable.
How much memory does gpt-oss 120B need?
Generic Android Phone (12GB RAM) does not have enough memory. At Q4_K_M the weights are ~59.03 GB; with KV cache and runtime overhead, budget ~62.4 GB at a 4k context. It is a Mixture-of-Experts model (117B total / 5.1B active), so all experts must stay in memory; memory tracks total params, not active params.
What is the best tool to run gpt-oss 120B 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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A live badge for your model card or README, updated as the data is. [](https://localmodel.run/can-i-run/gpt-oss-120b/android-generic-12gb) 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.