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Head to head · Decision models · October 2026 research run

Decider vs ScaleDown

Decider scores 69.5 (B) on agent readiness against ScaleDown's 48.6 (D), and leads in 5 of 7 scored categories. ScaleDown leads on security & auth and transparency & trust. Both do decision models.

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DeciderMark Marosi (Mapika) · Model API B69.5/100#188 of 1084 ScaleDownCarbon ScaleDown, Inc. · Model API D48.6/100#873 of 1084

Which one, for what

Decider B

Best for Local classification, routing, triage and checks where a team wants open weights in several sizes and a Jev-shaped route.

Ahead on

  • Reliability, 90 against 20
  • Schema & documentation, 78 against 69
  • Payments & pricing, 60 against 40
  • Maintenance & community, 87 against 56

Also in its favour

  • No key needed to call it
  • Open source

Watch for

The local server has no authentication option. It binds to 127.0.0.1 since 1.7.1

ScaleDown D

Best for Cheap, high-volume labelling, routing and yes or no checks where a probability is more useful than prose, and for pulling described fields with offsets from text, images or PDFs.

Ahead on

  • Security & auth, 48 against 38
  • Transparency & trust, 54 against 46

Also in its favour

  • A hosted endpoint, with nothing to install
  • Free to start without a card

Watch for

No status page, no published rate limits and no SLA outside enterprise contracts

Score by category

CategoryWeight this runDeciderScaleDownEdge
Reliability16%209020Decider +70
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.27869Decider +9
Agent ergonomics13%16.28076Decider +4
Security & auth14%17.53848ScaleDown +10
Payments & pricing10%12.56040Decider +20
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.88756Decider +31
Transparency & trust7%8.84654ScaleDown +8
Negative events≤150-2
TotalB 69.5/100D 48.6/100

Facts side by side

FactDeciderScaleDown
KindModel APIModel API
VendorMark Marosi (Mapika)Carbon ScaleDown, Inc.
Hosted endpointno (local only)https://api.scaledown.xyz
TransportsHTTPHTTP
AuthNoneAPI key
PricingFreePay per use
x402nono
LicenceApache-2.0 (code and weights)Proprietary hosted models under ScaleDown's Terms of Service. The langchain-scaledown integration is MIT
Read-only variant documentednono
llms.txtnoyes
Last release2026-10-072026-10-14
Terms last updatedno document linkedcouldn't be read
Privacy policy last updatedno document linkedcouldn't be read
Customer content may train modelscouldn't be read
Terms restrict automated accesscouldn't be read
Terms restrict benchmarkingcouldn't be read
Terms or service can change without noticecouldn't be read
Arbitration or class-action waivercouldn't be read
Popularity1.1k stars, 2.7k PyPI/wk0 stars

Verdicts

Decider

An Apache-2.0 decision model family with a dated changelog, passing CI, 21 package releases since 22 September 2026 and model cards that list measured regressions. One person maintains it, the local server has no authentication option, states over 32,768 tokens are cut without an error, and no security policy is published.

ScaleDown

Classify answers Jev-shaped choice, noul and score questions with probabilities, and Extract returns values with confidences and character offsets, at $0.05 per million input tokens with output free. There is no status page, no published rate limit and no public changelog, and the site's compliance claims contradict each other.

Before you call either

Decider

  1. Pin weights by Hub tag (v10, v2) when results must repeat. The main branch of each model repository changes with new versions
  2. Read x_p_max for the top probability. Since 1.3.0 confidence on choice and score answers follows TypeSafe's rescaled definition, not the top probability
  3. Keep the server on 127.0.0.1 or put an authenticating proxy in front. It has no key option
  4. Count state tokens before sending. Over 32,768 the state is cut silently, and /decide caps context at 1,536 tokens
  5. Split multi-step arithmetic or multi-hop judgements into several questions, and don't write long rules into a question. The README says both fail

ScaleDown

  1. Send several questions about one item in one /v1/scaledown call. Each becomes its own Classify call and the usage is summed
  2. Pin classify-1, extract-1 or summarize-1 once you've tuned thresholds on your own labelled cases
  3. Set context_chars to 0 and use top_n on Extract unless you need the 500 characters of context each side
  4. Set reasoning: false on /classify when you only need the label. The reasoning call bills its input at 2x
  5. Back off and retry on 429, 502 and 504. No limits are published and calls have no side effects

Questions

Which is better for AI agents, Decider or ScaleDown?

Decider scores 69.5 (B) on agent readiness against ScaleDown's 48.6 (D), and leads in 5 of 7 scored categories. ScaleDown leads on security & auth and transparency & trust.

Do Decider and ScaleDown need an API key?

Decider needs no key. ScaleDown needs an API key.

Can an agent call Decider and ScaleDown without installing anything?

No hosted endpoint is listed for Decider. ScaleDown has a hosted endpoint at https://api.scaledown.xyz.

Are Decider and ScaleDown open source?

Decider is open source (Apache-2.0 (code and weights)). No open-source release is listed for ScaleDown.

Other comparisons with Decider or ScaleDown

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