manjunathshiva/turboquant-mlx

Run models too big for your Mac's memory

LLM inference server with continuous batching & SSD caching for Apple Silicon — managed from the macOS menu bar

⚡ Native MLX Swift LLM inference server for Apple Silicon. OpenAI-compatible API, SSD streaming for 100B+ MoE models, TurboQuant KV cache compression, MACOS + iOS iPhone app.

Flash-MoE sidecar slot-bank runtime for large GGUF MoE models on Apple Silicon — llama.cpp fork

Swift + Metal MoE inference for Apple Silicon: Qwen 3.6 35B at 23.5–29.3 tok/s decode with 2.20× faster long-prompt prefill on a 24 GB M5; Gemma 4 26B in ~2 GB, DeepSeek-V4-Flash 284B, Inkling-Small 276B, native Mac app, CLI, and OpenAI-compatible server.

Running a big model on a small laptop

High-performance OpenAI and Anthropic compatible LLM inference server for Apple Silicon. Native MLX, continuous batching, multimodal models, MCP tool calling, and Claude Code support.

Qwen3.8-Flash-Next on Apple Silicon: an MLX engine that reads Strata's GGUF files and speaks its line protocol (unofficial)

Run LLMs with MLX