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ljupco/mlx-serve-macos-15-build-run
mlx-serve-macos-15-build-run is a machine learning model from ljupco. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for mlx.
Proven 2026-09-05 on macOS 15.7.7, M2 Max 96 GB, Apple clang 17 (CommandLineTools 16.4, no full Xcode at start) → working mlx-serve 26.9.1-dev serving Qwen3.8-Flash-Next (qwen4exp) 4-bit pack with native MTP at TG 27.…
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Updated Sep 7, 2026
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From the Hugging Face model README
Proven 2026-09-05 on macOS 15.7.7, M2 Max 96 GB, Apple clang 17
(CommandLineTools 16.4, no full Xcode at start) → 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.md — read this first; the TODO is the whole reproductionscripts/build-mlx-macos15.sh — MLX + mlx-c at deployment target 15.0 (NAX off)scripts/build-llama-b10472-macos15.sh — llama.cpp at mlx-serve's pinned tag b10472scripts/download-model.sh — fetch the 4-bit pack from HFscripts/verify-install.sh — every gate in one runscripts/run-mlxserve.sh — launch the server (MTP on, PLE streamed from disk)STATE-REPORT.md — full research state (llama.cpp PRs, alternatives, numbers)Related (not in this package):
$HOME/mlx-serve/ — the mlx-serve git clone we build from$HOME/mlx-serve-models/ddalcu/Qwen3.8-Flash-Next-MLX-Serve-4bit — the model pack (98 GiB, on NVME so the 30 GiB n-gram table streams from disk)This package exists because of mlx-serve by
David Dalcu — 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 —
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) —
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 — 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).