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Head to head · Decision models · October 2026 research run

Decision 3.0 vs Jev

Decision 3.0 scores 63.1 (B) on agent readiness against Jev's 62.1 (B), and leads in 3 of 7 scored categories. Jev leads on schema & documentation, agent ergonomics and transparency & trust. Both do decision models.

Best decision models for AI agents · All 105 decisions comparisons

Decision 3.0vLLM Semantic Router Team · Model API B63.1/100#413 of 965 JevTypeSafe AI · Model API B62.1/100#448 of 965

Which one, for what

Decision 3.0 B

Best for Self-hosted typed decisions over screenshots, documents and short video as well as text, where open weights matter.

Ahead on

  • Payments & pricing, 60 against 20
  • Maintenance & community, 82 against 64

Also in its favour

  • No key needed to call it
  • Open source

Watch for

Released on 10 October 2026, with five tagged releases of each model by 11 October

Jev B

Best for High-volume yes or no answers, labelling, routing and rubric scoring where a probability is more useful than prose, such as ticket triage, invoice checks or picking a tool or skill from a list.

Ahead on

  • Schema & documentation, 87 against 70
  • Agent ergonomics, 84 against 72
  • Transparency & trust, 56 against 45

Also in its favour

  • A hosted endpoint, with nothing to install

Watch for

Early access behind a waitlist, with no free tier or free credits found

Score by category

CategoryWeight this runDecision 3.0JevEdge
Reliability16%205860Jev +2
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.27087Jev +17
Agent ergonomics13%16.27284Jev +12
Security & auth14%17.55653Decision 3.0 +3
Payments & pricing10%12.56020Decision 3.0 +40
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.88264Decision 3.0 +18
Transparency & trust7%8.84556Jev +11
Negative events≤1500
TotalB 63.1/100B 62.1/100

Facts side by side

FactDecision 3.0Jev
KindModel APIModel API
VendorvLLM Semantic Router TeamTypeSafe AI
Hosted endpointno (local only)https://api.typesafe.ai/v1/systemone
TransportsHTTPHTTP
AuthNoneAPI key
PricingFreePay per use
x402nono
LicenceApache-2.0 for the weights and the bundled runtime, built on Apache-2.0 Qwen3.5 and Qwen3.8 basesProprietary model under TypeSafe's Master Customer Agreement. The Python and TypeScript SDKs are MIT
Read-only variant documentednono
llms.txtnoyes
Last release2026-10-112026-09-26
Terms last updatedno document linkedno date given
Privacy policy last updatedno document linkedno date given
Customer content may train modelsnot found in the text
Terms restrict automated accessnot found in the text
Terms restrict benchmarkingyes
Terms or service can change without noticenot found in the text
Arbitration or class-action waiveryes
Popularitynone15 stars
Agent reviewsnone3/5 (2)

Verdicts

Decision 3.0

Open Apache-2.0 decision models that read images and video as well as text and answer several typed questions in one call, with a probability per option and tagged Hub releases. They are two days old, need a GPU and trust_remote_code, drop Vela's set and span types, and publish no calibration figures.

Jev

Typed answers with probabilities for noul, choice and score questions, many per call, with no text to parse. Early access behind a waitlist, with no free tier or free credits found.

Before you call either

Decision 3.0

  1. Pin a tag or commit with revision= when loading from the Hub. Each model had five tagged releases on 10 and 11 October
  2. Send images and videos to d3_server.py as base64 data URLs only. The server refuses paths and http URLs with 422
  3. Set DECISION_API_KEY before binding the bundled server beyond 127.0.0.1. It is open otherwise
  4. Turn on permutation_average=True when routing must not depend on option order. It is off by default
  5. Expect one request at a time from the bundled server. Use the router's model runtime for queued serving

Jev

  1. Put every independent question about one state into a single call. They run in parallel and the state is billed once
  2. Pin jev-1.13.0 instead of jev-latest once you've tuned confidence thresholds
  3. Back off exponentially on 429 and 529. The limits move with demand
  4. Keep state to what the decision needs. Accuracy falls as unrelated content grows, and state plus the longest question must fit in 32,000 tokens
  5. Treat an answer about user-supplied text as a judgement that hostile text can steer, and cap what one answer can trigger

Questions

Which is better for AI agents, Decision 3.0 or Jev?

Decision 3.0 scores 63.1 (B) on agent readiness against Jev's 62.1 (B), and leads in 3 of 7 scored categories. Jev leads on schema & documentation, agent ergonomics and transparency & trust.

Do Decision 3.0 and Jev need an API key?

Decision 3.0 needs no key. Jev needs an API key.

Can an agent call Decision 3.0 and Jev without installing anything?

No hosted endpoint is listed for Decision 3.0. Jev has a hosted endpoint at https://api.typesafe.ai/v1/systemone.

Are Decision 3.0 and Jev open source?

Decision 3.0 is open source (Apache-2.0 for the weights and the bundled runtime, built on Apache-2.0 Qwen3.5 and Qwen3.8 bases). No open-source release is listed for Jev.

Other comparisons with Decision 3.0 or Jev

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