--- title: This is why Jev is so fast. | daily.dev description: An encoder-based model called Jev (transcription of an actual name, unclear spelling) generates an entire response in a single shot rather than token by token... canonical: https://daily.dev/posts/this-is-why-jev-is-so-fast--nmmhfwpt8 twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: This is why Jev is so fast. | daily.dev og:description: An encoder-based model called Jev (transcription of an actual name, unclear spelling) generates an entire response in a single shot rather than token by token... og:url: https://daily.dev/posts/this-is-why-jev-is-so-fast--nmmhfwpt8 og:image: https://api.daily.dev/og/posts/nMMHfwpt8.png og:image:alt: This is why Jev is so fast. 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. # This is why Jev is so fast. **[Gaurav Sen](https://daily.dev/sources/gkcs)** · 2 min read · 0 upvotes · 0 comments ## Summary An encoder-based model called Jev (transcription of an actual name, unclear spelling) generates an entire response in a single shot rather than token by token like GPT-style autoregressive models. This makes it much faster and well-suited for classification tasks, such as detecting a pothole in an image, and lets new output classes be added without retraining the whole model. However, it lacks token-by-token reasoning, so there's no way to evaluate or improve partial outputs mid-generation, meaning it won't replace GPT for reasoning-heavy tasks, only for decision and classification use cases. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### Why is an encoder-based model faster than GPT at generating responses? It generates the entire output object in one shot rather than token by token. GPT-style models predict one token at a time, feeding each output back as input for the next token, which is inherently sequential. An encoder converts the whole input into a single output representation in one pass, making it much faster, especially for tasks like classification such as detecting a pothole in an image. _Weighing model architectures for a project's latency needs is easier with daily.dev keeping you current on generation approaches._ ### Why can't encoder-based models replace GPT for reasoning tasks? They generate the entire response as a single object with no intermediate token-by-token steps, so there's no way to evaluate or revise partial output mid-generation. Token-by-token generation lets a model apply stronger reasoning strategies by assessing whether earlier parts of a response are good before continuing, an advantage encoders lack since their output is either fully accepted or rejected. _Understanding these trade-offs helps developers pick the right model for reasoning versus classification work, a topic daily.dev tracks closely._ --- Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#gpt](https://daily.dev/tags/gpt), [#classification](https://daily.dev/tags/classification) [View this post on daily.dev](https://daily.dev/posts/this-is-why-jev-is-so-fast--nmmhfwpt8) ```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":"TechArticle","headline":"This is why Jev is so fast.","url":"https://daily.dev/posts/this-is-why-jev-is-so-fast--nmmhfwpt8","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/this-is-why-jev-is-so-fast--nmmhfwpt8"},"datePublished":"2026-09-28T19:08:50.420Z","dateModified":"2026-09-29T19:41:42.712Z","description":"An encoder-based model called Jev (transcription of an actual name, unclear spelling) generates an entire response in a single shot rather than token by token...","image":"https://i.ytimg.com/vi/d9INaNO3Nrs/sddefault.jpg","thumbnailUrl":"https://i.ytimg.com/vi/d9INaNO3Nrs/sddefault.jpg","isAccessibleForFree":true,"articleSection":"Gaurav Sen","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"Gaurav Sen","logo":"https://media.daily.dev/image/upload/s--Ttjtrbgk--/f_auto,q_auto/v1780213730/logos/gkcs?_a=BAMAMiWQ0","url":"https://daily.dev/sources/gkcs"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/this-is-why-jev-is-so-fast--nmmhfwpt8","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":0},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"machine-learning,gpt,classification","timeRequired":"PT2M","video":{"@type":"VideoObject","name":"This is why Jev is so fast.","description":"An encoder-based model called Jev (transcription of an actual name, unclear spelling) generates an entire response in a single shot rather than token by token...","thumbnailUrl":"https://i.ytimg.com/vi/d9INaNO3Nrs/sddefault.jpg","uploadDate":"2026-09-28T19:08:50.420Z","duration":"PT2M","url":"https://api.daily.dev/r/nMMHfwpt8","embedUrl":"https://www.youtube.com/embed/d9INaNO3Nrs"}} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Gaurav Sen","item":"https://daily.dev/sources/gkcs"},{"@type":"ListItem","position":3,"name":"This is why Jev is so fast."}]} {"@context":"https://schema.org","@type":"FAQPage","@id":"https://daily.dev/posts/this-is-why-jev-is-so-fast--nmmhfwpt8#faq","mainEntity":[{"@type":"Question","name":"Why is an encoder-based model faster than GPT at generating responses?","acceptedAnswer":{"@type":"Answer","text":"It generates the entire output object in one shot rather than token by token. 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