MLX performance holds, ecosystem quality concerns rise

Hot take: MLX is active at the core-framework layer, but its user-facing model curation and troubleshooting loop looks underpowered compared with GGUF’s community machine.

• –The core project is still shipping (ml-explore/mlx released v0.31.1 on March 12, 2026), so this does not look abandoned.
• –Hugging Face’s `library=mlx` feed shows many recently updated models, which suggests broad ecosystem activity beyond one collection page.
• –The specific `mlx-community` Qwen-3.5 collection showing only the four largest variants reinforces the “curation lag” complaint.
• –Recent community benchmark threads keep surfacing practical gaps (prompt-caching behavior, quant/runtime edge cases), which can make “faster” feel worse in real workflows.
• –Net: MLX remains a strong Apple-native inference stack, but trust is being set by runtime quality and maintainer responsiveness, not peak tokens/sec.