drumih/turbo-fieldfare

Health v2 · maintenance only

Flags: young

Adoption not part of the score

6397 stars · 400 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

TurboFieldfare is a custom Swift + Metal runtime that runs Gemma 4 26B-A4B inference in roughly 2 GB of RAM on Apple Silicon Macs by streaming mixture-of-experts weights from SSD. It ships as a native Mac app, CLI, and local OpenAI-compatible server.

Use cases

• run a 26B LLM locally on an 8 GB MacBook
• on-device chatbot inference without cloud APIs
• serve a local OpenAI-compatible LLM endpoint on macOS
• run Gemma 4 with minimal RAM usage
• experiment with Metal GPU kernels for LLM inference
• private offline text generation on Apple Silicon

When to choose

• you have an M-series Mac with limited RAM and want large local LLM inference
• you want a model-specific optimized runtime rather than llama.cpp or MLX wrappers
• you want a native macOS app plus CLI and local server in one tool

When to avoid

• you need multi-model or cross-platform support
• you don't have Apple Silicon or macOS 26+
• you need fine-tuning or training, not just inference
• you can't spare ~15 GB of disk for the repacked model

Facets

application · maturity active

llm-inference gpu-computing cli gui large-language-models artificial-intelligence machine-learning cli metal apple-silicon gemma on-device-ai mixture-of-experts ssd-streaming low-memory local-llm openai-compatible-server macos swift gpu desktop

Member repositories

For agents

markdown · JSON · MCP: product_card(name="drumih/turbo-fieldfare")