Instructions to use ljupco/mlx-serve-macos-15-build-run with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use ljupco/mlx-serve-macos-15-build-run with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir mlx-serve-macos-15-build-run ljupco/mlx-serve-macos-15-build-run
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
mlx-serve on macOS 15.x β build & run package (Qwen3.8-Flash-Next with MTP)
Proven 2026-09-05 on macOS 15.7.7, M2 Max 96 GB, Apple clang 17
(CommandLineTools 16.4, no full Xcode at start) β working
mlx-serve 26.9.1-dev serving Qwen3.8-Flash-Next (qwen4_exp) 4-bit pack
with native MTP at TG 27.43 t/s / PP 29.6 t/s.
Model pack source: https://huggingface.co/ddalcu/Qwen3.8-Flash-Next-MLX-Serve-4bit mlx-serve upstream: https://github.com/ddalcu/mlx-serve/ (site: mlxserve.com)
This directory is the reproduction package. AGENTS.md is the entry point:
it explains why each step exists, lists the exact TODO order, the commands,
the verification gate for every step, and every failure we hit with its fix.
Files:
AGENTS.mdβ read this first; the TODO is the whole reproductionscripts/build-mlx-macos15.shβ MLX + mlx-c at deployment target 15.0 (NAX off)scripts/build-llama-b10472-macos15.shβ llama.cpp at mlx-serve's pinned tag b10472scripts/download-model.shβ fetch the 4-bit pack from HFscripts/verify-install.shβ every gate in one runscripts/run-mlxserve.shβ launch the server (MTP on, PLE streamed from disk)STATE-REPORT.mdβ full research state (llama.cpp PRs, alternatives, numbers)
Related (not in this package):
$HOME/mlx-serve/β the mlx-serve git clone we build from$HOME/mlx-serve-models/ddalcu/Qwen3.8-Flash-Next-MLX-Serve-4bitβ the model pack (98 GiB, on NVME so the 30 GiB n-gram table streams from disk)
Acknowledgements
This package exists because of mlx-serve by
David Dalcu β a remarkable piece of engineering. A native Zig server running
MLX-format models on Apple Silicon with OpenAI-, Anthropic-, Responses- and
Ollama-compatible APIs on one port, it ships a complete qwen4_exp engine β
hyper-connections, gated delta-net layers, QSA sparse attention, batched decode,
native MTP for the Qwen 3.5/3.6/3.8 family, and the n-gram PLE table designed to
stream from disk (ngram_table.bin, mmap'd, host-gathered, never resident) β
plus a published 4-bit pack and a 462-line engineering-gotchas log. Running a
176B-parameter model with speculative decoding on a MacBook was his work first;
this package only documents how to get it onto macOS 15, where the official
release binaries (built for macOS 26.2 / Metal 4.0) will not load. Thank you,
David β profusely.
Also credited: kernelpool (the qwen4-exp ds4 branch that proved the
Metal-graph port), AtomicChat (the AD-Q4_K_M quant), Unsloth (imatrix +
MTP sidecar GGUFs), and the llama.cpp contributors behind PRs #27742 and
#28015 (qwen4exp support and M2 Max Metal tuning).