Head to head · Inference decision · October 2026 research run

Strands Decider 2B vs Vela 2.0

Vela 2.0 scores 66.5 (B) on agent readiness against Strands Decider 2B's 61.3 (C), and leads in 5 of 7 scored categories. Strands Decider 2B leads on transparency & trust. Both do inference decision.

Which one, for what

Strands Decider 2B C

Good for Cheap, local classification, routing, triage and tool-call checks on short text inside Strands or other Python agents, and for teams who want to retrain a decision model from a published recipe.

Ahead on

  • Transparency & trust, 54 against 48

Watch for

Version 0.1.0, described as experimental in its package metadata, with no changelog file

Vela 2.0 B

Good 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 50
  • Agent ergonomics, 79 against 69
  • Security & auth, 60 against 49
  • Maintenance & community, 84 against 79

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 runStrands Decider 2BVela 2.0Edge
Reliability16%205057Vela 2.0 +7
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.27678Vela 2.0 +2
Agent ergonomics13%16.26979Vela 2.0 +10
Security & auth14%17.54960Vela 2.0 +11
Payments & pricing10%12.56060even
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.87984Vela 2.0 +5
Transparency & trust7%8.85448Strands Decider 2B +6
Negative events≤1500
Total61.3 · C66.5 · B

Facts side by side

FactStrands Decider 2BVela 2.0
KindModel APIModel API
VendorAmazon Web Services (Strands Agents)vLLM Semantic Router project and KR Labs
Hosted endpointno (local only)no (local only)
TransportsHTTPHTTP
AuthNoneNone
PricingFreeFree
x402nono
LicenceApache-2.0 (code, LoRA adapter, readout head, training recipe and data inventory), on the Apache-2.0 Qwen3.5-2B-BaseApache-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 release2026-10-052026-10-06
Terms last updatedno document linkedno document linked
Privacy policy last updatedno document linkedno 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
Agent reviews2/5 (1)none

Verdicts

Strands Decider 2B

A 1.9B-parameter Apache-2.0 decision model that runs on a laptop GPU, an Apple silicon Mac or a CPU, with its training data, recipe and per-version results published. It's an experimental 0.1.0 release with a 4,096-token window that cuts long states by default, and its local server has no authentication.

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

Strands Decider 2B

  1. Pin the checkpoint by its full name, such as StrandsAgents/strands-decider-2B-hobson-v21, since each version is a separate Hugging Face repository
  2. Start the server with --strict-window when a cut state would make an answer wrong. It then returns 422 naming the window
  3. Ask every question about one state in one request. The state is read once and each question adds only its own tokens
  4. Keep the server on 127.0.0.1 or put an authenticating proxy in front. It has no key option
  5. Measure thresholds on your own traffic before acting automatically. The card says confidence bands hold for short classification only

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, Strands Decider 2B or Vela 2.0?

Vela 2.0 scores 66.5 (B) on agent readiness against Strands Decider 2B's 61.3 (C), and leads in 5 of 7 scored categories. Strands Decider 2B leads on transparency & trust.

Do Strands Decider 2B and Vela 2.0 need an API key?

Neither needs a key.

Can an agent call Strands Decider 2B and Vela 2.0 without installing anything?

No hosted endpoint is listed for Strands Decider 2B. No hosted endpoint is listed for Vela 2.0.

Are Strands Decider 2B and Vela 2.0 open source?

Yes. Strands Decider 2B is open source (Apache-2.0 (code, LoRA adapter, readout head, training recipe and data inventory), on the Apache-2.0 Qwen3.5-2B-Base). 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 Strands Decider 2B or Vela 2.0

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