Dev Tools · 1h ago
Local AI Stack in 2026: Ollama and Qwen Survive, Autocomplete Dropped
A security engineer details their local AI setup mid-2026, running Ollama with two Qwen2.5-Coder models (1.5B and 7B) for different tasks. They dropped local autocomplete due to latency issues and purged unused models, keeping only what they actively use. The post highlights that switching costs and real-world performance matter more than benchmark scores.
Meridian48 take
The piece underscores a pragmatic truth: local AI adoption is held back not by model quality but by latency and maintenance overhead, which cloud services avoid.
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My Local AI Stack, Mid-2026: What Survived and What I Dropped →
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