--- title: 100x Faster, 90% Cheaper: Why Jev is Replacing OpenAI... description: A product pitch introduces Jev by TypeSafe AI, a 'System One' model that returns typed decisions (Choice, Score, Noul primitives) instead of generated text,... canonical: https://daily.dev/posts/100x-faster-90-cheaper-why-jev-is-replacing-openai-and-anthropic-kbcaqnmrs twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: 100x Faster, 90% Cheaper: Why Jev is Replacing OpenAI and Anthropic | daily.dev og:description: A product pitch introduces Jev by TypeSafe AI, a 'System One' model that returns typed decisions (Choice, Score, Noul primitives) instead of generated text,... og:url: https://daily.dev/posts/100x-faster-90-cheaper-why-jev-is-replacing-openai-and-anthropic-kbcaqnmrs og:image: https://api.daily.dev/og/posts/kbcaqnmRS.png og:image:alt: 100x Faster, 90% Cheaper: Why Jev is Replacing OpenAI and Anthropic og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # 100x Faster, 90% Cheaper: Why Jev is Replacing OpenAI and Anthropic **[AI](https://daily.dev/sources/ai)** · [@cristianolivera1](https://daily.dev/cristianolivera1) · 2 min read · 41 upvotes · 5 comments ## Summary A product pitch introduces Jev by TypeSafe AI, a 'System One' model that returns typed decisions (Choice, Score, Noul primitives) instead of generated text, claiming 70-500ms latency versus 2,000-5,000ms for LLMs like OpenAI and Anthropic models, zero cost versus $2.50-$15 per million tokens, and zero type errors. It proposes a 'Confidence-Threshold Routing' architecture where Jev handles high-confidence intake decisions and escalates low-confidence cases to heavier reasoning models or humans, claiming up to 90% cost reduction. ## Content Stop forcing your backend to read prose. Standard LLMs (like OpenAI Astra or Claude Sonnet) are built for sequential, token-by-token generation. They are slow, expensive, and require bloated parsing layers just to ensure they didn't hallucinate outside your requested JSON schema. **Jev by TypeSafe AI** (founded by Diogo Almeida, ex-OpenAI pioneer behind InstructGPT) takes the opposite approach. It is a **System One frontier model** that never writes a single sentence. Instead, it evaluates your entire state in a single parallel step and returns native, typed decisions with zero formatting failures. **The Blueprint: LLMs vs. Jev (System One)** **Engineering MetricFrontier LLMs (Astra / Fable)Jev (TypeSafe AI)Output Type**Text Strings (Requires Parsing)**Native Typed Decisions + ProbabilitiesSampling Engine**Sequential (Token-by-Token)**Parallel (Single-Step)Latency**2,000ms – 5,000ms**70ms – 500msOutput Cost**High ($2.50 - $15.00 / M)**$0.00 (Completely Free)Type Errors**Non-Zero (Breaks in Production)**0% by Construction** **How it Works: The 3 Native Primitives** Instead of throwing generic system prompts at a chat interface, Jev behaves like a **highly scaleable, intelligent **`if-else`** statement** using only three strict API primitive types: - `Choice`: Selects the exact match from an enum of up to 255 options. It returns the choice, individual probabilities per option, and a calibrated confidence score. - `Score`: Places data on a strict semantic scale from 2 to 10 levels described by words (e.g., rating customer frustration, returning precise floats like `1.4`). - `Noul`: A raw binary boolean response (Yes/No) delivered as a single probability float from 0 to 1. **Where It Fits in Your Agentic Workflow:** Jev is not a replacement for your core reasoning models; it’s the **gatekeeper of your architecture**. The most efficient pattern emerging in late 2026 is **Confidence-Threshold Routing**: 1. **The Intake:** Jev processes high-volume incoming webhooks, support tickets, or API requests in parallel. 2. **High-Confidence Path:** If Jev’s calibrated probability is above your threshold, your deterministic code handles the action instantly. 3. **Low-Confidence / Edge Cases:** If Jev flags a complex anomaly, the system escalates the request to a heavy reasoning model or a human reviewer. This architecture drops your AI operating costs by up to 90%, protects your API Gateway from latency spikes, and builds a strict, auditable boundary between autonomous actions and human oversight. ## Community discussion Top comments from developers on daily.dev. **@the\_polyglot** · 6 upvotes > how can it replace them ? They are two different forms of thinking, two different architectures with two different intents. > > Excited to fin real world uses for jev but its going to be another tool in the belt, anthropics going nowhere **@gabelg** · 2 upvotes > It doesn't replace the top LLMs. It augments them mostly. It replaces a subset of functions we currently use LLMs for that are not speed and cost optimized. > > It does open up a huge amount of possibilities for AI optimized choices. > > I use it at [mailkite.dev](http://mailkite.dev) to do the spam filtering, automatic email sorting into categories, tagging and flagging for LLM or human workflows. > > I also recently tried building it into a mac optimization tool and it works really well at very low cost. **@kevinmimir** · 0 upvotes > Will JEV become available to download? ## Similar posts on daily.dev - [What is Jev? How System One models could change AI agents : fireup.pro](https://daily.dev/posts/what-is-jev-how-system-one-models-could-change-ai-agents-fireup-pro-eqcqub8on) · FireUp · 1 upvotes · 0 comments --- Tags: [#llm](https://daily.dev/tags/llm), [#ai-agents](https://daily.dev/tags/ai-agents), [#openai](https://daily.dev/tags/openai) [View this post on daily.dev](https://daily.dev/posts/100x-faster-90-cheaper-why-jev-is-replacing-openai-and-anthropic-kbcaqnmrs) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"DiscussionForumPosting","mainEntityOfPage":"https://daily.dev/posts/100x-faster-90-cheaper-why-jev-is-replacing-openai-and-anthropic-kbcaqnmrs","headline":"100x Faster, 90% Cheaper: Why Jev is Replacing OpenAI and Anthropic","text":"A product pitch introduces Jev by TypeSafe AI, a 'System One' model that returns typed decisions (Choice, Score, Noul primitives) instead of generated text, claiming 70-500ms latency versus 2,000-5,000ms for LLMs like OpenAI and Anthropic models, zero cost versus $2.50-$15 per million tokens, and zero type errors. It proposes a 'Confidence-Threshold Routing' architecture where Jev handles high-confidence intake decisions and escalates low-confidence cases to heavier reasoning models or humans, claiming up to 90% cost reduction.","url":"https://daily.dev/posts/100x-faster-90-cheaper-why-jev-is-replacing-openai-and-anthropic-kbcaqnmrs","datePublished":"2026-09-21T10:45:08.718Z","dateModified":"2026-09-21T10:45:23.554Z","author":{"@type":"Person","name":"Cristian Olivera Chávez","url":"https://daily.dev/cristianolivera1","image":"https://lh3.googleusercontent.com/a/ACg8ocICzd1bW91kCFqI0PuT1IRi9n8e6m7C2_QMCxE2xLrx7d2Q5tY=s96-c","description":"Angular | NextJs | Tailwind | Laravel | Spring Boot","interactionStatistic":{"@type":"InteractionCounter","interactionType":{"@type":"EndorseAction"},"userInteractionCount":4750}},"image":"https://media.daily.dev/image/upload/s--Ud8fUoKo--/f_auto/v1789954304/posts/AiytAgdHX?_a=BAMAMicg0","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":41},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":5}],"comment":[{"@type":"Comment","text":"how can it replace them ? They are two different forms of thinking, two different architectures with two different intents.\nExcited to fin real world uses for jev but its going to be another tool in the belt, anthropics going nowhere","datePublished":"2026-10-02T15:29:32.985Z","url":"https://daily.dev/posts/kbcaqnmRS#c-4MiwCgEMD","author":{"@type":"Person","name":"Colin Rickels","url":"https://daily.dev/the_polyglot","image":"https://avatars.githubusercontent.com/u/7825706?v=4"},"interactionStatistic":{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":6}},{"@type":"Comment","text":"It doesn’t replace the top LLMs. It augments them mostly. It replaces a subset of functions we currently use LLMs for that are not speed and cost optimized.\nIt does open up a huge amount of possibilities for AI optimized choices.\nI use it at mailkite.dev to do the spam filtering, automatic email sorting into categories, tagging and flagging for LLM or human workflows.\nI also recently tried building it into a mac optimization tool and it works really well at very low cost.","datePublished":"2026-10-03T14:48:07.794Z","url":"https://daily.dev/posts/kbcaqnmRS#c-IwjiHJsjV","author":{"@type":"Person","name":"Gabe LG","url":"https://daily.dev/gabelg","image":"https://lh3.googleusercontent.com/a/ACg8ocKeHr5E3RohtHwNLCC5wxgdosCTHw2A6HgprnF_wls-nNYF0EB1=s96-c"},"interactionStatistic":{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":2}},{"@type":"Comment","text":"Will JEV become available to download?","datePublished":"2026-10-06T20:56:19.173Z","url":"https://daily.dev/posts/kbcaqnmRS#c-lHXSWX2EP","author":{"@type":"Person","name":"Kevin","url":"https://daily.dev/kevinmimir","image":"https://avatars.githubusercontent.com/u/127798963?v=4"}}],"isPartOf":{"@type":"WebPage","url":"https://daily.dev/squads/ai","name":"AI"}} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"AI","item":"https://daily.dev/squads/ai"},{"@type":"ListItem","position":3,"name":"100x Faster, 90% Cheaper: Why Jev is Replacing OpenAI and Anthropic"}]} ```