Liquid AI's local agent model: test the job, not the token speed
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A fast local model can still leave an engineer with a slow, expensive job. Liquid AI's new LFM2.5-24B-A2B reports strong results on selected agent tests, but its 24B total parameters, 2B active parameters and high-concurrency server throughput measure different things.
Augur explains which tasks merit a local trial, why vendor benchmarks don't establish savings, and how tool permissions and dependency checks affect the decision. The episode focuses on local-agent routing and supply-chain safeguards. Google's geospatial agent and Anthropic's election-use analysis remain in the…
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