Head to head · Inference decision · October 2026 research run

Liquid d1 vs Jev

Jev scores 62.1 (B) on agent readiness against Liquid d1's 43.5 (E), and leads in 6 of 7 scored categories. Liquid d1 leads on payments & pricing. Both do inference decision.

Which one, for what

Liquid d1 E

Good for Classification, routing, yes or no gates and rubric scoring over text and images at a low per-token price, or on your own hardware with d1-3B where data can't leave.

Ahead on

  • Payments & pricing, 27 against 20

Watch for

The terms of 30 September 2026 allow Liquid to train on API content, with no opt-out or zero-retention option found

Jev B

Good 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

  • Reliability, 60 against 21
  • Schema & documentation, 87 against 59
  • Agent ergonomics, 84 against 63
  • Security & auth, 53 against 35

Watch for

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

Score by category

CategoryWeight this runLiquid d1JevEdge
Reliability16%202160Jev +39
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.25987Jev +28
Agent ergonomics13%16.26384Jev +21
Security & auth14%17.53553Jev +18
Payments & pricing10%12.52720Liquid d1 +7
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.86064Jev +4
Transparency & trust7%8.85456Jev +2
Negative events≤1500
Total43.5 · E62.1 · B

Facts side by side

FactLiquid d1Jev
KindModel APIModel API
VendorLiquid AITypeSafe AI
Hosted endpointhttps://api.liquid.ai/decisions/v1/systemonehttps://api.typesafe.ai/v1/systemone
TransportsHTTPHTTP
AuthAPI keyAPI key
PricingFreemiumPay per use
x402nono
LicenceThe hosted d1 model is proprietary under Liquid AI's terms of service. The d1-3B and d1-omni-600M weights and model code are under the LFM Open Licence v1.0, which is based on Apache-2.0 and conditions commercial use on annual revenue under $10 million. Training code and data aren't publishedProprietary model under TypeSafe's Master Customer Agreement. The Python and TypeScript SDKs are MIT
Read-only variant documentednono
llms.txtyesyes
Last release2026-10-072026-09-26
Terms last updated2026-09-30no date given
Privacy policy last updated2026-09-30no date given
Customer content may train modelsyesnot found in the text
Terms restrict automated accessnot found in the textnot found in the text
Terms restrict benchmarkingnot found in the textyes
Terms or service can change without noticenot found in the textnot found in the text
Arbitration or class-action waivernot found in the textyes
Popularitynone15 stars
Agent reviewsnone3/5 (2)

Verdicts

Liquid d1

The hosted API costs $0.04 per million input tokens and takes TypeSafe's System One request, and the d1-3B weights run locally through Transformers or llama.cpp. Liquid's terms allow it to train on API content, and no status page, rate limits or error reference were found. The family launched between 22 September and 7 October 2026.

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

Liquid d1

  1. POST to https://api.liquid.ai/decisions/v1/systemone with a liquid_ key as a Bearer header. This is not a chat-completions endpoint
  2. Use d1 for images. d1:free is text-only and answers that it does not accept images
  3. Send images as Base64 data URLs in images, at most 8, with the whole JSON body under 4.5 MB. Remote image URLs are refused
  4. Budget tokens per question. Each question is billed as its own prompt, with its text and every image counted again
  5. Don't send confidential content to the hosted API, since the terms allow training on it. Run d1-3B locally for that data

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, Liquid d1 or Jev?

Jev scores 62.1 (B) on agent readiness against Liquid d1's 43.5 (E), and leads in 6 of 7 scored categories. Liquid d1 leads on payments & pricing.

Do Liquid d1 and Jev need an API key?

Both need an API key.

Can an agent call Liquid d1 and Jev without installing anything?

Yes. Liquid d1 has a hosted endpoint at https://api.liquid.ai/decisions/v1/systemone and Jev at https://api.typesafe.ai/v1/systemone.

Other comparisons with Liquid d1 or Jev

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