AI Agent StoreNace.AI · Native API contract verified
Drex v2.0 · native API
Choose from allowed answers without generating a paragraph: route a ticket, classify a document or return a probability for each option.
Released 2026-10-06 · First reviewed 2026-10-13 · Checked 2026-10-15.
We still need comparable independent tests. You can compare the confirmed features and limits below, but we cannot yet give this version an Agent Fit or Practical Value rating. Test it on records with known answers, including cases that should go to a person.
What you can use today
Token prices measure the small pieces of text the model reads or produces. Capacity is the amount the service accepts in a request; check the limits below for any fallback to another model. A dash means the rate is unverified.
Exact provider API ID: drex-v2.0. Send text state and up to 512 typed questions to /v1/systemone. Drex v2.0 returns probabilities, not a written explanation. Validate those probabilities on examples from your own workflow.
The provider dates v2.0 October 6 and moved drex-latest and omitted-model requests to it on October 12. Use the exact ID drex-v2.0 to select this version; unknown names beginning drex- or nacedm- can select the current default.
Drex v2.0 accepts up to 131,072 tokens of shared information, and up to 262,144 including the longest question. It allows up to 512 questions and 4,194,304 bytes for the serialized request. Requests above a limit are refused; v2.0 no longer hands long requests to v1.5.
Output: Yes/no probabilities, multiple-choice probabilities and ordered rating scores. No generated explanation. Compare decision models, limits and input costs ↗
Native v2.0 costs $0.06 per million billed input tokens, with no output, request or question fee. Only successful evaluations are charged. Use the returned usage totals to compare bills. Use actual billed usage and the model named in each response to check your estimate.
Provider release and specifications ↗
Check availability and plans ↗
More setup and licensing details ↗
Test it before switching
Give each model the same examples, tools and definition of success. Record correct outcomes, response time, retries and total cost. Check whether confidence scores match the answers you can verify.
Compare caching and long-context costs ↗