MLX beats Ollama for complex MoE agent stacks

// 45d agoINFRASTRUCTURE

MLX beats Ollama for complex MoE agent stacks

ANNOUNCEMENT PRODUCT GITHUB PRODUCT HUNT

A developer reports that switching from Ollama to raw MLX for a 12-agent Qwen 35B stack on M1 Max fixed long-form generation "word-salad" issues and throughput bottlenecks. The move sacrifices convenience for in-process sectional generation and fine-grained sampler control.

// ANALYSIS

Power users are outgrowing the "Ollama wrapper" layer as agentic workflows demand deeper model control.

–Sectional generation is the MoE savior, preventing repetition collapse in Qwen 35B without the latency of HTTP round-trips.
–Raw MLX throughput is essential for "thinking" models, often doubling tokens-per-second compared to legacy local backends.
–Direct Python bindings enable sophisticated in-process orchestration like priority queues and per-call sampler adjustments.
–The tradeoff highlights a split between "it just works" users and developers building high-uptime, specialized agent stacks.

// TAGS

llminferenceagentapple-siliconmlxollamaqwenopen-source

DISCOVERED

45d ago

2026-04-24

PUBLISHED

45d ago

2026-04-24

RELEVANCE

8/ 10

AUTHOR

sleepy_quant

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