go-mlx

Native Apple Metal GPU inference via mlx-c CGO bindings, implementing the inference.Backend and inference.TextModel interfaces from go-inference for Apple Silicon (M1-M4). Supports Gemma 3, Qwen 2/3, and Llama 3 architectures from HuggingFace safetensors format, with fused Metal kernels for RMSNorm, RoPE, and scaled dot-product attention, KV cache management, LoRA fine-tuning with AdamW, and batch inference. A Python subprocess backend (mlxlm) is provided as a CGO-free alternative. Platform-restricted: darwin/arm64 only; a no-op stub compiles on all other platforms.

Module: forge.lthn.ai/core/go-mlx Licence: EUPL-1.2 Language: Go 1.25

Quick Start

import (
    "forge.lthn.ai/core/go-inference"
    _ "forge.lthn.ai/core/go-mlx"  // registers "metal" backend via init()
)

model, err := inference.LoadModel("/Volumes/Data/lem/safetensors/gemma-3-1b/")
defer model.Close()

for tok := range model.Generate(ctx, "Hello", inference.WithMaxTokens(256)) {
    fmt.Print(tok.Text)
}

Documentation

• Architecture — CGO binding, model architectures, weight loading, KV cache, attention, batch inference, LoRA training, mlxlm backend
• Development Guide — prerequisites (mlx-c CMake build), CGO flags, test patterns, benchmarks
• Project History — completed phases, commit hashes, known limitations

Build & Test

go generate ./...        # builds mlx-c C library (required first time)
go test ./...
go build ./...

Licence

European Union Public Licence 1.2 — see LICENCE for details.