State of Local AI · 2026
The shift is happening
Our annual report on local AI adoption across 12,000 Gotchi users. Model trends, hardware benchmarks, and the economics of running AI locally.
Finding #1
73% now run AI fully locally
Up from 41% in 2025. The quality gap between open-source and frontier models has narrowed enough that most users no longer need cloud fallback for daily tasks. Llama 3.1 70B is the most popular model, followed by DeepSeek V3 and Qwen 2.5.
Local-first adoption
41%
2025
73%
2026
Finding #2
Average user saves $480/year
Based on usage patterns of 47M tokens/month average, users who switched from cloud AI services save an estimated $480/year in subscription and API costs. Teams of 10 save over $4,800 annually.
Yearly spendunlimited usage
Cloud APIs$720+/yr
Cloud subscription$240/yr
Gotchi€49.99/yr
Finding #3
Agent adoption grew 340%
The most popular agent workflows: email triage (62% of agent users), daily standup recaps (48%), code review automation (35%), and meeting preparation (29%). Scheduled agents run 3.2x more often than manually triggered ones.
Agent adoptionyear over year
1×
2025
4.4×
2026
Finding #4
Apple Silicon leads local AI
89% of Gotchi users run on Apple Silicon (M1–M4). Average inference speed: 74ms p50 for Llama 3.1 70B on M3 Pro. M4 Max delivers 2.3x throughput improvement over M2 Max.
Local inferenceOffline
Your prompt
Model reasoning
GPU compute
Knowledge base
Everything stays on your machine
Download the full report
Get the complete State of Local AI 2026 report with benchmarks, methodology, and predictions.
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