Head to head · Decision models · October 2026 research run

Decision 3.0 vs Drex 1.5

Drex 1.5 scores 69.7 (B) on agent readiness against Decision 3.0's 63.1 (B), and leads in 5 of 7 scored categories. Decision 3.0 leads on payments & pricing and maintenance & community. Both do decision models.

Best decision models for AI agents · All 105 decisions comparisons

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 40
  • Maintenance & community, 82 against 65

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

Drex 1.5 B

Best for Routing, triage and yes or no gates inside an agent, where the caller supplies the options and acts on the probabilities. Suited to hosted use at a low per-token price, or to open weights where the licence fits.

Ahead on

  • Reliability, 80 against 58
  • Schema & documentation, 88 against 70
  • Agent ergonomics, 85 against 72
  • Security & auth, 65 against 56
  • Transparency & trust, 63 against 45

Also in its favour

  • A hosted endpoint, with nothing to install

Watch for

The rank 1 claim comes from Nace's own run on Decision Index 0.3.1, and Drex is not on the public board for 0.3 or 0.2.1.

Score by category

CategoryWeight this runDecision 3.0Drex 1.5Edge
Reliability16%205880Drex 1.5 +22
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.27088Drex 1.5 +18
Agent ergonomics13%16.27285Drex 1.5 +13
Security & auth14%17.55665Drex 1.5 +9
Payments & pricing10%12.56040Decision 3.0 +20
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.88265Decision 3.0 +17
Transparency & trust7%8.84563Drex 1.5 +18
Negative events≤150-2
TotalB 63.1/100B 69.7/100

Facts side by side

FactDecision 3.0Drex 1.5
KindModel APIModel API
VendorvLLM Semantic Router TeamNace AI, Inc. (Nace.AI)
Hosted endpointno (local only)https://console.nace.ai/v1/systemone
TransportsHTTPHTTP
AuthNoneAPI key
PricingFreeFreemium
x402nono
LicenceApache-2.0 for the weights and the bundled runtime, built on Apache-2.0 Qwen3.5 and Qwen3.8 basesHosted API under the Nace AI Terms of Service, last updated 5 May 2026. Weights under the Nace AI Open RAIL-M licence (modified, version 1.0, October 2026), which is not an open-source licence. Businesses above $1 million in revenue or funding need a separate commercial licence, and competing products are excluded. The bundled code/kev package, derived from Jared Palmer's Kev (https://github.com/jaredpalmer/kev), and the GitHub repository are Apache-2.0, and the agent skill is MIT.
Read-only variant documentednono
llms.txtnoyes
Last release2026-10-112026-09-28
Terms last updatedno document linked
Privacy policy last updatedno document linked
Customer content may train models
Terms restrict automated access
Terms restrict benchmarking
Terms or service can change without notice
Arbitration or class-action waiver
Popularitynone318 npm/wk, 156 PyPI/wk

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.

Drex 1.5

The hosted endpoint has a public OpenAPI document, published limits and pinned model versions, at $0.05 per million input tokens with no output charge. The #1 under 10B claim rests on Nace's own run, since Drex is absent from both public boards. Weights carry Open RAIL-M, which requires a commercial licence above $1 million in revenue or funding.

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

Drex 1.5

  1. Call https://console.nace.ai/v1/systemone with Authorization: Bearer nace_sk_..., and pin model drex-v1.5 rather than drex-latest in production.
  2. Stop on 402 insufficient_credit or 402 payment_required until credit is topped up or the unpaid invoice is paid.
  3. Retry 429 and 529 after retry-after-ms. On a 422 for an unknown model, use one of the ids the error message lists.
  4. Keep state below 131,072 tokens and the body below 1,048,576 bytes, and send at most 512 questions per request.
  5. Keep the key on a server. A key in browser code is exposed, and the /v1 routes send no Access-Control-Allow-Origin header.
  6. Check usage.input_tokens and the usage CSV after retries, since /v1/systemone documents no idempotency key.

Questions

Which is better for AI agents, Decision 3.0 or Drex 1.5?

Drex 1.5 scores 69.7 (B) on agent readiness against Decision 3.0's 63.1 (B), and leads in 5 of 7 scored categories. Decision 3.0 leads on payments & pricing and maintenance & community.

Do Decision 3.0 and Drex 1.5 need an API key?

Decision 3.0 needs no key. Drex 1.5 needs an API key.

Can an agent call Decision 3.0 and Drex 1.5 without installing anything?

No hosted endpoint is listed for Decision 3.0. Drex 1.5 has a hosted endpoint at https://console.nace.ai/v1/systemone.

Are Decision 3.0 and Drex 1.5 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 Drex 1.5.

Other comparisons with Decision 3.0 or Drex 1.5

Machine-readable

For companies

Do agents find, use and choose your tools?

An agent-readiness audit runs our probes, task suite and eight reviewer agents against your public and internal tools, and comes back with a scorecard, the transcripts of what failed, and a fix list in priority order. From $2,500, re-run included. We never take payment to move a rank. We do help companies earn one.