TypeSafe
Jev Latest
Total Context
32K
Max Output
N/A
Released
N/A
jev-1.14Jev 1.14 is TypeSafe's System One model for fast, structured decision-making in software. It evaluates text and application state against developer-defined questions, returning choices, yes/no probabilities, and scores that applications can use directly. Built for classification, routing, and automated workflows, it helps developers turn natural-language judgments into actionable outputs and supports evaluating multiple questions in parallel within a single request.
Context Window
32K tokens
Release Date
Oct 14, 2026
Modalities
| Input Price | Output Price |
|---|---|
| $0.042/M | $0/M |
Reasoning
Tool calling
Temperature parameter
Attachments
Knowledge Base
Endpoint Protocols
Verified strengths and model characteristics.
Returns choices, rubric scores and yes/no probabilities for focused judgments that application code can combine.
Evaluates independent questions against shared context in parallel, reducing repeated processing in decision workflows.
Adds a Box question type that locates one image target with normalized coordinates and confidence; image features remain experimental.
Practical workloads supported by official model information.
Classify a support request, assess urgency and route it to a handler or reviewer using application-defined thresholds.
Score retrieved passages for relevance before selecting evidence for a separate answer-generating model.
Prototype semantic image crops by checking target presence and locating it with Box; review results before production use.
curl 'https://us-api.tokenhub.com/v1/systemone' \
-X 'POST' \
-H "Authorization: Bearer $TOKENHUB_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "jev-1.14",
"questions": {
"department": {
"criteria": {
"billing": "Charges and refunds",
"technical": "Product defects"
},
"instructions": "Which team should handle this ticket?",
"type": "choice"
},
"needs_refund": {
"instructions": "Does the customer explicitly request a refund?",
"type": "noul"
},
"urgency": {
"criteria": [
"Routine",
"Needs attention",
"Critical"
],
"instructions": "How urgent is this ticket?",
"type": "score"
}
},
"state": {
"ticket": "I was charged twice. Please refund the duplicate charge."
}
}'Model selection, limitations, pricing and TokenHub integration.
Jev 1.14 is TypeSafe AI’s System One decision model update, released as jev-1.14.0 through jev-preview. It produces typed judgments for software.
Choose it for focused routing, classification and scoring with predefined answers. Use a generative model for prose, code or extended reasoning explanations.
No. Calibration describes groups of predictions, not guaranteed correctness for one decision. Validate thresholds on representative data, including difficult and non-English inputs.
Images and Box are experimental. Box returns coordinates even when the target is absent. Default context is 64K per request and 32K per question; opt-in 262K context is slower and less accurate.
If a route is available, follow TokenHub’s exact model ID and decision-request example. Confirm endpoint, question types and experimental-header support; do not assume standard chat request semantics.
TypeSafe lists $0.042 per million input tokens and no output-token charge. Check TokenHub’s current route pricing and availability separately.
Use one API key to access Jev 1.14 and more AI models through TokenHub.
Jev 1.14 — Media and Demos
Verified public posts and videos; community findings are not guarantees.
X (Twitter)
TypeSafe AI ·
TypeSafe announces Jev 1.14 and identifies images, Box and longer context as preview features.
we announced Jev 1.14 on 10.14 at 1:14pm PT 🔥 a new and improved model, along with experimental features for our dreamers: • images • a new box type • longer context surprise, Jev was already able to see you! 👁️ BUT our bar for production-grade intelligence is quite high, so builders beware, these are preview features. enter the ~*~ danger zone ~*~ at your own risk. 🚨
https://pbs.twimg.com/media/HUocW4abQAAsHO4.jpgView originalTypeLLM ·
TypeLLM announces API support for Jev 1.14 image bounding-box outputs.
Jev 1.14 introduces image bounding box generation. TypeLLM now supports it too, directly through our API. Try it now: https://typellm.ai/examples/find-objects https://t.co/OJKfQ8pBId
https://pbs.twimg.com/tweet_video_thumb/HUpjNW_a0AA2zJT.jpgView originalKC ·
A developer discusses Jev 1.14’s experimental features and possible image-ad filtering applications.
Read full post
Jev 更新到 1.14 了,最意外的是 1.13 原来一直都支持多模态,只是之前没开 现在请求头加一个 danger zone 的 flag 就能传图片,而且图片能放在 state、instructions,甚至 criteria 里。我之前用 Jev 做了个识别广告的 TG 群 bot,官方送的 5 美元额度到现在还没用完。当时就在想能不能让它也识别图片广告,这下可以试试了。我在做的 SSH 客户端 Hatoba 也加了实验性的 Jev 支持,用 System One 的方式自动判断工具指令的危险程度 还多了一个 box 类型,直接返回一个 bounding box,是 Jev 第一个不只是用来做判断的类型,只有 1.14 能用。长上下文也可以手动解锁了,Jev 实际支持的长度比生产环境开放的长很多,之前是官方故意限制的 不过这几个都是实验性的,官方自己也说还不够稳,不建议上生产,图片的效果也比纯文本差。1.14 本身是各方面的小改进,多语言提升最大,现在用 jev-preview 能试,jev-latest 一周后才切过去 他们一向不喜欢公开 benchmark,这次倒是放出了自己的内部评测,只拿开放权重模型来比
Reddit
Released JEV 1.14 w/vision capability
Timetraveler842 ·
A community release recap links Jev 1.14’s official announcement and experimental-feature documentation.
Read full post
Official announcement: What's new 🖼️ Images: put images anywhere in your request, in the state, in questions, even in criteria. JPEG and PNG for now. 📦 Box: our new question type, available on Jev 1.14, specifically for requests containing images. Ask Jev to find something in an image and it'll return a bounding box for it. 📈 Long context: We now support per-question and per-request context limits up to 262K tokens. 🧪 Danger zone: we heavily prioritize reliability for our builders, but we know some of you are dreamers too looking to access these preview features. If that's you, opt-in for access via the appropriate Danger Zone header to use them. ✨ Plus improvements to the core model. All the details are in the blog. Start here 📖 Blog: https://typesafe.ai/blog/jev-1-14 🖼️ Images docs: https://docs.typesafe.ai/images#turning-on-images 📦 Box docs: https://docs.typesafe.ai/primitives/box#box 📈 Context docs: https://docs.typesafe.ai/models#long-context Favorite moments Diogo calling "It's up! Go, go, go!" when the API went live mid stage Allie's live demos catching a tiny glint of necklace Kevin searching his screen with a picture of a banana Wally, found, at 0.47 confidence The great "jev lotion" debate, still unresolved You're already building Within an hour we saw smart crops in Sanity Studio, a hallucination checker, an Agent Zero plugin, spam filtering on a mail server and yes, Where's Wally. Keep it coming in <#1483217545040232493>! Thank you for being here. Get out there and Jev Jev Jev 🩷
Jev 1.14.0 is bluffing on the hard question
shaun117 ·
A community evaluation reports that Jev 1.14’s calibration varies with question difficulty.
View originalSemantic hotspot and crop in a CMS with the new multimodal mode for Jev
knutmelvaer ·
A Sanity CMS prototype combines target-presence checks and Jev’s new Box output for semantic image cropping.
View originalYouTube
Tekoäly rakentaa sovelluksen ja analysoi jalkapalloa | Jev 1.14
Immo Salo
A Jev 1.14 application demo evaluates football-video frames and displays structured decisions with confidence.
View originalJev 1.14.0公開!画像・box型・262kトークンの長文を「danger zone」の実験機能として解禁
AIすきかも
A Japanese explainer reviews Jev 1.14’s release, image input, Box and experimental long context.
View originalJev 1.14 voit les images : utile, mais encore en chantier
Gia Gang
A French explainer examines Jev 1.14 visual localization, documented limitations and pricing.
View original