oMLX boosts Apple Silicon LLM performance with KV cache

oMLX, an open-source LLM inference server for Apple Silicon, has demonstrated significant performance improvements, particularly in handling large models and complex workflows. Community benchmarks and local tests highlight oMLX's advantages over alternatives like Ollama and LM Studio, especially in scenarios involving coding agents and persistent KV caching. The server's ability to leverage SSDs for KV cache dramatically reduces time-to-first-token (TTFT), making models like Claude Code and Qwen3-Coder-Next much more usable locally. oMLX also shows faster model loading times and lower end-to-end latency in multi-turn conversations compared to Ollama. AI

IMPACT oMLX's optimizations, particularly SSD KV caching, significantly improve local LLM usability on Apple Silicon, potentially accelerating adoption for developers and researchers.

RANK_REASON The article details performance benchmarks and technical optimizations for an open-source LLM inference server, presenting research-level findings on its capabilities and comparisons with competitors.

Read on dev.to — LLM tag →

• Apple Silicon
• Claude Code
• GLM-5
• LM Studio
• M3 Ultra
• M4 Max
• MiniMax-M2.5
• Ollama
• OpenClaw
• Qwen3.5-35B-A3B
• Qwen3-Coder-Next-80B

• infra
• product

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