Typed AI vs generative: when to use each

A blog post published by Jev argues that enterprise AI tasks split into two model types: generative LLMs, which produce free text at $2-50 per million tokens with latency in seconds, and "typed" models that return predefined values such as yes/no, a 0-10 score or a closed-list category at $0.042 per million tokens with 70-500ms latency. Jev cites a 100,000-query-per-day pipeline in which routing only the 20% of cases needing text generation to an LLM (Sonnet 5.5) cuts daily cost to roughly $15 from about $200 for an all-LLM architecture. The post positions Jev's launch as the concrete typed alternative to LLMs for classification, risk scoring and spam detection, while reserving generative models for tasks requiring reasoning and free-text output.

Until September 2026, “AI model” meant LLM: a model that generates text token by token. With the launch of Jev https://soamee.com/en/blog/jev-system-one-ai-typed-no-hallucinations , there’s a concrete alternative for a significant portion of enterprise tasks: models that return typed values with probabilities instead of free text. Two paradigms, two problems Generative AI LLMs An LLM receives text and produces text. Flexible but can hallucinate. Cost: $2-50/M tokens. Latency: seconds. Typed AI System One A typed model receives data and returns predefined format values: yes/no, score 0-10, a category from a closed list. Can’t generate anything outside the defined schema. Cost: $0.042/M tokens Jev . Latency: 70-500ms. Decision map by task | Task | AI type | Why | |---|---|---| | Classify emails by intent | Typed | Closed output sales, support, spam | | Reply to the email | Generative | Free text output | | Score contract risk | Typed | Numeric output 0-10 | | Explain why it’s risky | Generative | Free text argumentation | | Detect spam | Typed | Binary output | | Classify support ticket | Typed | Categorical output | | Resolve support ticket | Generative | Requires reasoning and text | The dividing line: if the output is a value from a defined set, typed AI. If the output is free text, LLM. Mixed pipeline The most efficient architecture uses each type where it performs best. For a system processing 100,000 queries/day: | Architecture | Daily cost approx. | |---|---| | All LLM Sonnet 5.5 | ~$200 | | Mixed typed + LLM only when needed | ~$15 | The LLM only runs on the 20% of cases requiring text generation. The rest uses typed AI at $0.042/M tokens. For a complete model overview, see AI model map October 2026 https://soamee.com/en/blog/ai-model-map-october-2026 . Our AI agents https://soamee.com/en/services/ai-agents team builds mixed pipelines. Request a free consultation https://soamee.com/en/free-consultation and we’ll analyze your case.