Head to head · Decision models · October 2026 research run

Microsoft-Decision-1 vs Vela 2.0

Vela 2.0 scores 66.5 (B) on agent readiness against Microsoft-Decision-1's 39 (E), and leads in every scored category. Both do decision models. Microsoft-Decision-1 is cheaper for decision models, $0 against $0 per 1M tokens.

Best decision models for AI agents · All 91 decisions comparisons

Which one, for what

Microsoft-Decision-1 E

Best for Routing, classification, prioritisation and rubric checks over text, where a fixed set of options and a low price per token matter more than generated text.

Also in its favour

  • Cheaper for decision models, $0 against $0 per 1M tokens

Watch for

Public preview only. Microsoft's post gives no general availability date and states no licence for the hosted model

Vela 2.0 B

Best for Self-hosted routing and guardrail checks in one call, where span offsets for personal data or unsupported claims matter.

Ahead on

  • Reliability, 57 against 30
  • Schema & documentation, 78 against 43
  • Agent ergonomics, 79 against 50
  • Security & auth, 60 against 52
  • Payments & pricing, 60 against 20
  • Maintenance & community, 84 against 40
  • Transparency & trust, 48 against 32

Also in its favour

  • No key needed to call it
  • Open source

Watch for

No version tags on the four Hub repositories, and the 4B and 9B weights were replaced in place on 3 October 2026

Score by category

CategoryWeight this runMicrosoft-Decision-1Vela 2.0Edge
Reliability16%203057Vela 2.0 +27
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.24378Vela 2.0 +35
Agent ergonomics13%16.25079Vela 2.0 +29
Security & auth14%17.55260Vela 2.0 +8
Payments & pricing10%12.52060Vela 2.0 +40
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.84084Vela 2.0 +44
Transparency & trust7%8.83248Vela 2.0 +16
Negative events≤1500
TotalE 39/100B 66.5/100

Facts side by side

FactMicrosoft-Decision-1Vela 2.0
KindModel APIModel API
VendorMicrosoftvLLM Semantic Router project and KR Labs
Hosted endpointno (local only)no (local only)
TransportsHTTPHTTP
AuthOAuth or keyNone
PricingPay per useFree
Price for decision modelsfreefree
x402nono
LicenceNot stated. The announcement and OpenRouter's model page name no licence, and no weights repository was found.Apache-2.0 (weights, code and documentation). The 0.3B's tokeniser keeps the Gemma Terms of Use, and training data keeps its own licences
Read-only variant documentednono
llms.txtnono
Last release2026-10-092026-10-06
Terms last updatedno document linkedno 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
Popularitynone6.1k stars

Verdicts

Microsoft-Decision-1

Microsoft publishes $0.042 per million input tokens, with output free, and the model is callable through Microsoft Foundry and OpenRouter. It is in public preview. No licence, model-specific retention statement, rate limit or deprecation policy was found, and the Foundry route needs an Azure deployment and an Entra token. Latency and accuracy figures are Microsoft's claims.

Vela 2.0

One self-hosted call answers routing, prompt-attack, personal-data and unsupported-claim questions with probabilities and character offsets, under Apache-2.0 with SHA-256 manifests. The models are days old and carry no Hub version tags, and the three larger sizes keep 74 to 89 per cent of their Decision 2.0 bases on the Jev Decision Index by the authors' figures.

Before you call either

Microsoft-Decision-1

  1. Use OpenRouter's Decisions method, not an OpenAI chat-completions SDK. OpenRouter says chat completions SDKs will not work with this model
  2. On Foundry, send the request to the deployment's /providers/microsoft/v1/systemone path with a Microsoft Entra token for https://cognitiveservices.azure.com/.default, not an API key
  3. Take the deployment name from the Foundry quickstart before the first call. Microsoft says to confirm the route and authentication header, and the pages reviewed do not give the name
  4. Keep each request within OpenRouter's 32,768-token context and send only fixed options, since the model is not intended for open-ended generation
  5. Measure latency and calibration on your own labelled cases before relying on Microsoft's latency and 'nine times out of 10' statements

Vela 2.0

  1. Pin a commit hash with revision= when loading from the Hub. The repositories have no tags and main has changed since launch
  2. Send the served name in model, for example vllm-sr/Vela-2.0-4B. The bundled server answers 422 to any other name
  3. Name span questions pii, halu or toxic, or set "head": "router", to get the trained router head. Other labels go to the broad head
  4. Keep input under 16,384 tokens a sequence (8,192 on the 0.3B). The bundled server answers 413 when the questions alone don't fit
  5. Set VELA2_API_KEY before binding the bundled server beyond 127.0.0.1, and keep the model runtime on a trusted network

Questions

Which is better for AI agents, Microsoft-Decision-1 or Vela 2.0?

Vela 2.0 scores 66.5 (B) on agent readiness against Microsoft-Decision-1's 39 (E), and leads in every scored category.

Which is cheaper for decision models, Microsoft-Decision-1 or Vela 2.0?

Microsoft-Decision-1, at free against free for Vela 2.0. These are the vendors' published prices for the job.

Do Microsoft-Decision-1 and Vela 2.0 need an API key?

Microsoft-Decision-1 takes an API key or an OAuth sign-in. Vela 2.0 needs no key.

Can an agent call Microsoft-Decision-1 and Vela 2.0 without installing anything?

No hosted endpoint is listed for Microsoft-Decision-1. No hosted endpoint is listed for Vela 2.0.

Are Microsoft-Decision-1 and Vela 2.0 open source?

No open-source release is listed for Microsoft-Decision-1. Vela 2.0 is open source (Apache-2.0 (weights, code and documentation). The 0.3B's tokeniser keeps the Gemma Terms of Use, and training data keeps its own licences).

Other comparisons with Microsoft-Decision-1 or Vela 2.0

Machine-readable

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