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Apple Intelligence pairs a 3-billion-parameter on-device model with a server model

Apple introduced Apple Intelligence on June 10, 2024, built on a roughly 3-billion-parameter language model that runs on the device and a larger model that runs on Apple silicon servers through Private Cloud Compute. The on-device model uses a 49K token vocabulary, the server model 100K.

Apple compresses the on-device model with a mix of 2-bit and 4-bit weights, averaging 3.7 bits per weight, and says an option at 3.5 bits per weight costs no significant quality. On an iPhone 15 Pro the company reports a time to first token of about 0.6 milliseconds per prompt token and 30 tokens per second, both measured before token speculation.

Rather than ship a separate model per feature, Apple swaps LoRA adapters on top of the shared base model. The adapters are stored in 16 bits and, at rank 16, take tens of megabytes each. Apple says human graders preferred its models over comparable ones including GPT-3.5, GPT-4, Llama, Mistral and Gemma across its evaluations.

Pipeline diagram running from data, preprocessing, pre-training, post-training and optimisation to Apple Foundation Models, with a stack of adapters on top
Diagram: Apple.
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  2. LLMFarm runs llama.cpp models offline on iOS and macOS
  3. ExecuTorch alpha runs Llama 2 7B on iPhone 15 Pro and Galaxy phones