text model · MiniMax · iOS
Can I run MiniMax-M1-80k on iPhone Air?
No. MiniMax-M1-80k needs ~284.6 GB even at Q4_K_M, but iPhone Air only has ~8 GB usable.
Needs ~284.6 GB even at Q4_K_M, but only ~8 GB is usable.
That figure is at a 4k context and moves about ±15% as context length changes.
The gap is about 276.6 GB: MiniMax-M1-80k needs roughly 284.6 GB at Q4_K_M and iPhone Air leaves only about 8 GB usable for a model. No single tracked device has enough memory; MiniMax-M1-80k needs a multi-GPU or high-memory rig.
- Q4_K_M needed
- ~284.6 GB
- Usable on device
- ~8 GB
- Device memory
- 12 GB
Which quant fits
How to run it
On iOS use Apple Foundation Models (Built into iOS 26, ~3B on-device model, zero download, fully private.).
- Parameters
- 456B (MoE, 45.9B active)
- Q4_K_M size
- 278.7 GB
- Context
- 1000k
- Memory
- 12 GB unified
- Usable for weights
- ~8 GB
- Best runtime
- llama.cpp + Metal (via PocketPal or Off Grid app)
What you can run instead
FAQ
Can iPhone Air run MiniMax-M1-80k?
No. MiniMax-M1-80k needs ~284.6 GB even at Q4_K_M, but iPhone Air only has ~8 GB usable.
How much memory does MiniMax-M1-80k need?
iPhone Air does not have enough memory. At Q4_K_M the weights are ~278.7 GB; with KV cache and runtime overhead, budget ~284.6 GB at a 4k context. It is a Mixture-of-Experts model (456B total / 45.9B active), so all experts must stay in memory; memory tracks total params, not active params.
What is the best tool to run MiniMax-M1-80k on iOS?
On iPhone and iPad, Apple Foundation Models (Built into iOS 26, ~3B on-device model, zero download, fully private.) is the standard choice. Phones realistically run 1B-4B class models. Anything larger thermally throttles or OOMs.
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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.