We love how this doomo doomonstrates real-time intelligence and what can be doone with code + AI! ~10 calls/sec = ~$7/hour
API & Models
model field
The required request field that selects which model handles the call; accepts versioned IDs and aliases.
- Category
- API & Models
- Also known as
- —
- Related terms
- 4
- Directory entries
- 2
- Docs
- docs.typesafe.ai
- Added
- 2026-09-24
Definition
The model field names the model that performs the evaluation. Examples use jev-latest, which is also the SDK default, but a pinned version such as jev-1.13.0 is accepted whether or not it appears in the models list.
The response echoes the versioned ID that actually answered, so logs can record which build produced each result even when a request used an alias.
Tagsapimodels
Related terms
Definitions that connect to this one.
Model aliasA name like jev-latest that resolves to a versioned model ID and can move when a new release ships.API & Modelsjev-latestThe default model alias in the SDKs and docs: the most recent stable official Jev release, currently jev-1.13.0.API & Modelsjev-1.13.0The current versioned Jev build: $42 per billion input tokens, a 64k context, and 250,000 tokens per second.API & ModelsSystem One endpointThe single HTTP endpoint that evaluates a state against typed questions: POST https://api.typesafe.ai/v1/systemone.API & Models
From the directory
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.
Sites & GuidesDocs#official#docs#models
Official
The raw HTTP contract behind every SDK: POST a state plus typed noul, choice, and score questions to /v1/systemone, and get one answer per question, with error codes and retry guidance.
Sites & GuidesDocs#official#docs#api
Official
From the community
Posts from builders shipping with Jev right now.
Jev plays Doom at ~10 calls/sec for ~$7/hour
Jev plays Super Mario Bros.
got @typesafeai’s new model Jev to play Super Mario Bros. fast inference + structured outputs makes it surprisingly good for real time use cases. I'm excited to see what can be done with these new models!
LLMs generate answers, Jev makes decisions
this is the easiest way to understand Jev: LLMs generate answers. Jev makes decisions. that sounds like a small difference, but it actually changes the entire use case. say you give a normal LLM this: “here’s a user, their account history, payment behavior, support chats, Show more
@CompleteSkeptic
After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x
Arbitrary classification as a primitive
Jev is cool not because it re-invented classification, but because it makes ARBITRARY classification into a type-safe programmable primitive. A general purpose zero shot decision model whose native interface is RUNTIME-DEFINED typed decisions, optimized for that exact interface
If you called Yann LeCun an idiot for saying we need to move beyond LLMs and build something new, you are banned from using Jev.
How Jev makes agents faster and cheaper
Jev solved local harness/model routing I use a combination of Claude Code, Codex and Opencode as my local agentic stack and routing to other harnesses was always enforced in the system prompt/rules With a deterministic hook that Claude Code can decide before delegation, Jev Show more
500 emails for 3.5 cents
Yeah Jev by @typesafeai is very cool. It classified 500 emails in seconds. And it costed 3.5 cents.