Skip to content

Jev Models & Reimplementations

Jev 1.14: Images, Box, and the Danger Zone

Jev Day shipped a routine model bump and a deliberate widening of the API: images on both models, a box question type on 1.14 only, and 262k context, all behind danger-zone headers.
Published
Category
Jev Models & Reimplementations
Resources cited
7
Reading time
4 min
Tags#release#vision#danger-zone#models

Jev Day shipped two things at once: a routine model bump and a deliberate widening of what the API accepts. Jev 1.14.0 is the routine part — small improvements everywhere, the largest expected in multilingual support. The rest is new surface area for builders who want to prototype: images, the box question type, and 262k context, all behind headers TypeSafe calls the danger zone.

What is actually stable

jev-1.14.0 ships as jev-preview at the same price and default context as 1.13.0: $0.042 per million input tokens, output free, 64k per request and 32k per question. jev-latest stays on 1.13.0 for about a week, then moves. TypeSafe intends 60 days' warning before 1.13.0 is formally deprecated and 30 days for 1.14.0, with a deprecation policy landing first. If you tuned thresholds against a version, pin the versioned ID and move on your schedule — the model alias glossary covers why.

Images were there all along

The surprise in the post is that jev-1.13.0 was multimodal the whole time; TypeSafe just did not expose it. Images now ride in an assets map keyed by a reference string, and the reference can sit anywhere the JSON interface allows — in state, in instructions, or in criteria. That composability is the interesting part: an option description can carry a reference image, and so can a Noul's true/false criteria.

The limits are real: PNG or JPEG stills, 256 to 1568 pixels per side, 16 MiB per file, 32 MiB per request body shared after processing. And TypeSafe's own warning is blunt — all models, Jev included, perform worse on images than on text, so decompose into the simplest possible questions.

Box is the first type that is not a decision

Every Jev question type until now mapped to a branch: Choice to a switch, Noul to an if, Score to a sort. Box returns four edges as fractions of the image plus a confidence — it answers where, not which. It needs 1.14.0 (or jev-preview) and the images header, and it takes no criteria.

One design detail decides how you use it: Box always returns a box. An absent target still gets four edges, so the documented pattern pairs it with a Noul presence check. TypeSafe's own small test on 36 painting crops, each cutting off part of the target, shows the shape of the problem: four per-edge Noul questions caught 30 cut-off crops, a single "is all of it inside" question caught 26, and drawing the box as an outline and asking about it caught 20.

The danger zone is a contract marker

The headers — TypeSafe-Danger-Zone-Images: true and TypeSafe-Danger-Zone-Long-Context: true — are TypeSafe's way of splitting reliability from experimentation. Features behind them will persist and improve, but the docs say plainly that format, limits, and accuracy can change between releases. For a production system the header is a flag that a request sits outside the reliability bar; for a prototype it is a cheap way to test whether a workflow is worth building properly later.

262k is permission, not advice

The context change is the most tempting one to misuse. Both caps rise to 262k with the long-context header, on 1.13.0 and 1.14.0, at the same per-token price — but the docs say the mode is slower and less accurate than staying inside the defaults, and the release post still strongly recommends limiting context. The shorter cap was a product choice; treat the header as a pressure valve for the rare long request, not a new default.

What to do this week

  • Pin jev-1.13.0 or jev-1.14.0 explicitly if thresholds depend on a version; log the response's model field.
  • Try images and Box on a throwaway workflow — the box study and imajev-4b are two community starting points.
  • Keep the rejection and presence checks around any Box work: a box for a missing target is still a box.
  • Re-run your evals against 1.14.0 before jev-latest moves, since the multilingual claims are TypeSafe's own and its internal chart is self-described as biased.

The headline is not the model bump. It is that Jev's interface now reaches past text and past decisions — carefully, behind headers, with the company saying out loud that the features are not ready. That is a more honest launch posture than most.

From the Jev directory

The resources behind this article.

The Jev Day release post: Jev 1.14.0 under jev-preview plus three danger-zone features — composable images on both models, the box question type on 1.14 only, and opt-in 262k context.
Jev Guides & ArticlesArticle#official#release#vision
Official
The experimental image-input reference: PNG or JPEG files in a top-level assets map, referenced by string anywhere in state, instructions, or criteria, behind the TypeSafe-Danger-Zone-Images header.
Jev Practices & PatternsDocs#official#docs#vision
Official
The box question type: one bounding box per question, returned as four edges that are fractions of the image, plus confidence, with no criteria field and no not-found value.
Jev Practices & PatternsDocs#official#docs#vision
Official
MarkTechPost's write-up of the Jev 1.14 release: images, a box question type and 262k long context as experimental danger-zone features, unchanged $0.042 per million input token pricing, and TypeSafe's own note that none are production-ready.
Jev Media & TalksArticle#community#news#images
Community
0GitHub stars
0xRinne's MIT-licensed field report on using TypeSafe Jev 1.14's Box type and image input to spot AI-image hallucinations, across seven pipeline versions v1-v7b, with a live Vercel demo and raw score JSON.
Jev Tools & CLIs#community#research#hallucination-detection
Mohit Garg's Apache-2.0 vision-language decision model on Qwen/Qwen3.5-4B, the recommended default of the imajev family: it reads photos against records and text, returning calibrated probabilities and a trained can't tell.
Jev Models & Reimplementations#community#open-models#vision-language
Community
The model card for jev-1.13.0: $42 per billion input tokens with free output, a 64k context, 250k tokens per second, and how to list the models your account can call.
Jev Guides & ArticlesDocs#official#docs#models
Official
Back to all articles

More Jev articles

How Pydantic AI, Mastra, TanStack AI, DSPy, Spring AI, and LiteLLM expose Jev: where the typed decision sits in the loop, what each integration returns, and which big frameworks are only adjacent.
Jev Integrations & Adapters#agents#frameworks#integrations
Read article
Tool menus can outgrow the context that reads them. The catalog's Jev-based routers and gates narrow the list: benchmarked tool search, per-tool scoring, fail-closed approvals, and WebMCP in the browser.
Jev Agents & MCP#mcp#tool-routing#agents
Read article

From the Jev AI model community

Posts from builders shipping with Jev right now.

Follow @typesafeai