REDDIT · REDDIT// 9d agoINFRASTRUCTURE

MLX vision workloads hit macOS memory wall

This Reddit post reports that document-image analysis with Qwen3.5 vision models runs out of RAM when served through MLX in LM Studio on a Mac with about 50GB available, while the same workload works with GGUF. The poster suspects an MLX-specific memory behavior in the vision path and is looking for confirmation or a known workaround, since MLX prefill is otherwise much faster on Apple Silicon.

// ANALYSIS

Hot take: this reads like a runtime/memory-management issue in the MLX vision stack, not a model-size problem.

–The symptom is format-specific: GGUF works, MLX fails, which points to backend allocation behavior rather than the model itself.
–Vision workloads are usually much heavier on transient memory than text-only inference, so image preprocessing/prefill may be amplifying peak usage.
–On Apple Silicon, unified memory can make “available RAM” feel generous until a single spike crosses the line.
–The practical tradeoff is clear: MLX buys speed, but the vision path may still be too memory-hungry for larger document images or certain Qwen3.5 variants.

// TAGS

mlxvision-language-modelsqwenlm-studiomacosramunified-memoryinference

DISCOVERED

9d ago

2026-04-02

PUBLISHED

9d ago

2026-04-02

RELEVANCE

8/ 10

AUTHOR

MrPecunius