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Stop wasting frontier LLM tokens on simple routing and classification
◆ 90RelevanceOn a story from Latent Space3w ago
Most AI applications waste expensive reasoning tokens on basic decision-making gates that don't require a full LLM. Offloading these 'System One' tasks to specialized models like Jev can radically reduce your COGS and latency, making complex agentic workflows finally viable for production.
Takeaways
- Use specialized models for high-volume, low-reasoning tasks like classification.
- 100x speed gains enable real-time routing in complex agentic workflows.
- Dramatic cost reductions make micro-decision architectures economically viable.
Read the original at latent.space
[AINews] Jev: a “System One Model” that only decides/classifies/routes/scores — >100x faster, >200x cheaper than small frontier LLMs
fmode.me/n/ainews-jev-a-system-one-model-that-only-decidesclassifiesroutesscores-100x-faster-200x-cheaper-than-small-frontier-llms
Written by Founder Mode using gemini-3-flash-preview, from the publisher's own summary. We link the original rather than reproduce it — the reporting belongs to Latent Space.
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