TurboFieldfare is an open-source Swift + Metal runtime that runs Google's Gemma 4 26B-A4B instruction-tuned model in approximately 2 GB of RAM on any Apple Silicon Mac, including 8 GB models. Instead of loading the full 14.3 GB model into memory, it keeps only the 1.35 GB shared core and FP16 KV cache resident, streaming required MoE experts from SSD on demand. The project includes a native SwiftUI Mac app, CLI, streaming model installer, and an OpenAI-compatible loopback server. Benchmarks show 5.1–6.3 tok/s on an 8 GB M2 MacBook Air and 31–35 tok/s on an M5 Pro. The runtime uses custom Metal kernels for quantized GEMV, attention, MoE, normalization, RoPE, and sampling, with 4-bit MLX affine weights and an 8-bit router. Requires macOS 26, Metal 4, and Swift 6.2.
