{ "data": { "a": { "slug": "strands-decider", "name": "Strands Decider 2B", "vendor": "Amazon Web Services (Strands Agents)", "vendorUrl": "https://strandsagents.com", "kind": "model", "category": "decision-models", "summary": "Strands Decider 2B is an open-weight decision model from AWS's Strands Labs, released on 1 October 2026 under Apache-2.0. It answers typed yes or no, choice and score questions with probabilities, and runs locally from a Python package.", "url": "https://www.anchorterminal.com/tools/strands-decider", "markdownUrl": "https://www.anchorterminal.com/tools/strands-decider.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/strands-decider.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/strands-decider.json", "repo": "https://github.com/strands-labs/strands-decider", "license": "Apache-2.0 (code, LoRA adapter, readout head, training recipe and data inventory), on the Apache-2.0 Qwen3.5-2B-Base", "transports": [ "http" ], "packages": [ { "registry": "pypi", "name": "strands-decider" } ], "auth": "none", "authNotes": "No account. `strands-decider serve` binds to 127.0.0.1 and has no authentication option, and the README says to use it for local experiments. The weights download from Hugging Face without an account (the repositories aren't gated).", "pricing": "free", "pricingNotes": "Free and open source, with nothing to buy. You pay for your own hardware. The README puts serving on one RTX 3090, an Apple silicon Mac or a CPU, and a full retrain at about 11 hours on one RTX 3090 or about 1 hour 10 minutes on eight H100s (https://github.com/strands-labs/strands-decider). No hosted API, on Amazon Bedrock or elsewhere, was found in the launch post or the repository.", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402. Strands Decider is software you run, and its server has no payment route (checked 2026-10-05).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-05" }, "docsUrl": "https://github.com/strands-labs/strands-decider#readme", "capabilities": [ "inference.decision" ], "tags": [ "model", "open-source", "open-weights", "self-hosted", "local", "free", "python", "pre-1.0" ], "lastRelease": "2026-10-05", "graded": true, "anchor": { "graded": true, "score": 61.3, "grade": "C", "agentReady": false, "rank": 327, "ranked": true, "rankOf": 629, "categoryRank": 7, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 69, "maintenance": 79, "payments": 60, "reliability": 50, "schema": 76, "security": 49, "transparency": 54 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-10-05" }, "negative": 0, "verdict": "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.", "bestFor": "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.", "strengths": [ "Apache-2.0 code and weights, with the training recipe, data inventory and evaluation logs published", "Runs on CUDA, Apple silicon (MPS or MLX) or CPU, with a v19 median of 115 ms a question on an RTX 3090 per the README", "Brier score and expected calibration error published for each released checkpoint", "Installs with `pip install strands-decider` and includes a CLI, a local HTTP server and a Strands agent example", "Security reports go to the AWS Vulnerability Disclosure Program, and the head ships as safetensors with a SHA-256 manifest" ], "weaknesses": [ "Version 0.1.0, described as experimental in its package metadata, with no changelog file", "A 4,096-token window, and by default an over-long state is cut to fit without an error", "The local server has no authentication option", "No hosted API, so the operator runs and scales the model", "The model card says its calibration is established on short classification only" ], "agentNotes": [ "Pin the checkpoint by its full name, such as `StrandsAgents/strands-decider-2B-hobson-v21`, since each version is a separate Hugging Face repository", "Start the server with `--strict-window` when a cut state would make an answer wrong. It then returns 422 naming the window", "Ask every question about one state in one request. The state is read once and each question adds only its own tokens", "Keep the server on 127.0.0.1 or put an authenticating proxy in front. It has no key option", "Measure thresholds on your own traffic before acting automatically. The card says confidence bands hold for short classification only" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 1, "avgRating": 2, "history": [ { "basis": "public evidence", "confidence": "low", "grade": "C", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 61.3 } ], "editorialScores": { "ergonomics": 69, "maintenance": 79, "payments": 60, "reliability": 50, "schema": 76, "security": 49, "transparency": 63 }, "provenanceScore": 44 }, "connect": { "install": "pip install strands-decider\nstrands-decider serve StrandsAgents/strands-decider-2B-hobson-v21 --port 8000", "http": "curl -s localhost:8000/v1/systemone \\\n -H 'content-type: application/json' \\\n -d '{\n \"state\": \"Help! My payouts have been failing for 3 days!\",\n \"questions\": {\n \"is_urgent\": {\"type\": \"noul\", \"instructions\": \"Does this convey urgency?\"}\n }\n }'" }, "letme": { "capability": "https://letme.dev/inference.decision", "tool": "https://letme.dev/strands-decider" }, "area": "models", "provenance": { "legalEntity": "Amazon Web Services, Inc.", "domain": "strandsagents.com", "domainRegistered": "2025-05-15", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-10-05", "notes": [ "The repository's SECURITY.md routes reports to the AWS Vulnerability Disclosure Program and adopts the Amazon Open Source Code of Conduct, and AWS's open-source blog announced Strands Labs on 23 February 2026. The legal entity is inferred from those pages. The licence names no copyright holder.", "strandsagents.com was registered on 15 May 2025 per RDAP. Its /.well-known/security.txt returned 404.", "Software you run, so there's no hosted endpoint, terms or privacy policy to check. The Apache-2.0 licence stands in for terms.", "No changelog file or GitHub release tags in the repository. Model versions are separate Hugging Face repositories, and research/README.md in the repository lists each training run." ], "score": 44 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/strands-decider.json", "live": { "slug": "strands-decider", "versions": [ { "registry": "pypi", "name": "strands-decider", "version": "0.1.0", "released": "2026-10-01", "seenAt": "2026-10-08T16:30:33.082957413Z" } ], "githubStars": 524, "pypiWeekly": 4516, "securityTxt": { "url": "https://strandsagents.com/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-08T15:39:09.928660277Z" }, "updatedAt": "2026-10-08T16:30:33.271392417Z" } }, "answer": "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 \u0026 trust.", "b": { "slug": "vela", "name": "Vela 2.0", "vendor": "vLLM Semantic Router project and KR Labs", "vendorUrl": "https://vllm-sr.ai", "kind": "model", "category": "decision-models", "summary": "Vela 2.0 is a family of four open-weight decision models from the vLLM Semantic Router project and KR Labs, released on 6 October 2026 under Apache-2.0 for routing, safety checks, personal-data spans and hallucination checks.", "url": "https://www.anchorterminal.com/tools/vela", "markdownUrl": "https://www.anchorterminal.com/tools/vela.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/vela.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/vela.json", "repo": "https://github.com/vllm-project/semantic-router", "license": "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", "transports": [ "http" ], "packages": [ { "registry": "pypi", "name": "vllm-sr" } ], "auth": "none", "authNotes": "No account. The weights are public and ungated on Hugging Face. The bundled `vela2_serve.py` binds to 127.0.0.1 and ignores the Authorization header unless `VELA2_API_KEY` is set, after which it requires `Authorization: Bearer \u003ckey\u003e` and answers 401 otherwise. The router's model runtime has no authentication and publishes on 127.0.0.1 unless `--host` is passed.", "pricing": "free", "pricingNotes": "Free and open source, with nothing to buy and no hosted API. Hardware is the owner's cost. The 0.3B runs on a CPU, and the cards put GPU parameter memory at about 17 GB for the 4B. The router docs list about 32 GB for the 9B (checked 2026-10-08).", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402. Vela 2.0 is software the owner runs, and neither server has a payment route (checked 2026-10-08).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 6054, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-08" }, "docsUrl": "https://huggingface.co/collections/vllm-sr/vela-20", "openapi": "https://raw.githubusercontent.com/vllm-project/semantic-router/main/src/model-runtime/vllm_srun/api/openapi.yaml", "capabilities": [ "inference.decision", "guard.pii", "guard.injection", "guard.moderation", "guard.self-host" ], "tags": [ "model", "open-source", "open-weights", "self-hosted", "local", "free", "python", "openapi" ], "lastRelease": "2026-10-06", "graded": true, "anchor": { "graded": true, "score": 66.5, "grade": "B", "agentReady": false, "rank": 219, "ranked": true, "rankOf": 629, "categoryRank": 4, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 79, "maintenance": 84, "payments": 60, "reliability": 57, "schema": 78, "security": 60, "transparency": 48 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-08" }, "negative": 0, "verdict": "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.", "bestFor": "Self-hosted routing and guardrail checks in one call, where span offsets for personal data or unsupported claims matter.", "strengths": [ "Five question types in one request (choice, noul, score, set and span), with span answers as labelled character offsets and a probability each", "Apache-2.0 weights, code and documentation, ungated on Hugging Face, with safetensors files and a SHA256SUMS manifest in the three decoder repositories", "Two serving routes. A bundled FastAPI server on `POST /v1/systemone`, and the router's model runtime with an OpenAPI 3.0.3 contract and Prometheus metrics", "The model cards disclose evaluation protocol, including that the 0.3B release selection considered test results and that SQuAD v2 isn't zero-shot", "The router's release note lists where the 0.3B default is behind Vela 1.0, with numbers, and how to restore each Vela 1.0 model" ], "weaknesses": [ "No version tags on the four Hub repositories, and the 4B and 9B weights were replaced in place on 3 October 2026", "Loading with `transformers` needs `trust_remote_code=True`, which runs Python from the model repository", "The router's `vllm-sr serve MODEL` engine mode is newer than the 0.4.0 stable release and needs the development channel", "By the authors' figures the 4B scores 31.63 on the Jev Decision Index 0.2.1 against 42.55 for its Decision 2.0 base", "The model runtime has no authentication, and the bundled server is open unless `VELA2_API_KEY` is set" ], "agentNotes": [ "Pin a commit hash with `revision=` when loading from the Hub. The repositories have no tags and `main` has changed since launch", "Send the served name in `model`, for example `vllm-sr/Vela-2.0-4B`. The bundled server answers 422 to any other name", "Name span questions `pii`, `halu` or `toxic`, or set `\"head\": \"router\"`, to get the trained router head. Other labels go to the broad head", "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", "Set `VELA2_API_KEY` before binding the bundled server beyond 127.0.0.1, and keep the model runtime on a trusted network" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 66.5 } ], "editorialScores": { "ergonomics": 79, "maintenance": 84, "payments": 60, "reliability": 57, "schema": 78, "security": 60, "transparency": 68 }, "provenanceScore": 27 }, "connect": { "install": "pip install torch \"transformers\u003e=5.17\" safetensors tokenizers numpy fastapi uvicorn\n# from a local snapshot of vllm-sr/Vela-2.0-4B\npython vela2_serve.py --model . --device cuda --port 8001", "http": "curl -s localhost:8001/v1/systemone -H 'content-type: application/json' \\\n -d '{\"model\":\"vllm-sr/Vela-2.0-4B\",\"state\":\"My card was charged twice and the parcel never arrived.\",\"questions\":{\"issues\":{\"type\":\"set\",\"instructions\":\"Which issues does the customer report?\",\"criteria\":{\"billing\":\"payments, charges, refunds or invoices\",\"shipping\":\"delivery of an order or a parcel\",\"login\":\"signing in, passwords or account access\"}}}}'" }, "letme": { "capability": "https://letme.dev/inference.decision", "tool": "https://letme.dev/vela" }, "area": "models", "provenance": { "legalEntity": "", "domain": "vllm-sr.ai", "domainRegistered": "2026-07-13", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://vllm-sr.ai/docs/release-notes/vela-2-0-built-in-signals", "securityTxt": "none", "checked": "2026-10-08", "notes": [ "An open-source project with no company named as publisher. The site footer reads vLLM Semantic Router Team, and the model cards credit KR Labs and vLLM Semantic Router.", "RDAP gives 13 July 2026 as the registration date of vllm-sr.ai.", "Software the owner runs, so there's no hosted endpoint, terms or privacy policy. The Apache-2.0 licence stands in for terms.", "vllm-sr.ai/.well-known/security.txt returns 404. SECURITY.md in the repository takes private reports through GitHub Security Advisories.", "The weights are on huggingface.co under the vllm-sr organisation, and the code for the router and its model runtime is at github.com/vllm-project/semantic-router." ], "score": 27 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/vela.json", "live": { "slug": "vela", "versions": [ { "registry": "github", "name": "vllm-project/semantic-router", "version": "v0.4.0", "released": "2026-09-27", "seenAt": "2026-10-08T16:33:55.54175052Z" }, { "registry": "pypi", "name": "vllm-sr", "version": "0.4.0", "released": "2026-09-27", "seenAt": "2026-10-08T16:33:55.414998665Z" } ], "githubStars": 6055, "pypiWeekly": 16024, "securityTxt": { "url": "https://vllm-sr.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-08T15:38:46.503839021Z" }, "updatedAt": "2026-10-08T16:33:55.54175052Z" } }, "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Amazon Web Services (Strands Agents)", "b": "vLLM Semantic Router project and KR Labs", "name": "Vendor" }, { "a": "no (local only)", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "None", "b": "None", "name": "Auth" }, { "a": "Free", "b": "Free", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Apache-2.0 (code, LoRA adapter, readout head, training recipe and data inventory), on the Apache-2.0 Qwen3.5-2B-Base", "b": "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", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-10-05", "b": "2026-10-06", "name": "Last release" }, { "a": "no document linked", "b": "no document linked", "name": "Terms last updated" }, { "a": "no document linked", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "", "b": "", "name": "Customer content may train models" }, { "a": "", "b": "", "name": "Terms restrict automated access" }, { "a": "", "b": "", "name": "Terms restrict benchmarking" }, { "a": "", "b": "", "name": "Terms or service can change without notice" }, { "a": "", "b": "", "name": "Arbitration or class-action waiver" }, { "a": "none", "b": "6.1k stars", "name": "Popularity" }, { "a": "2/5 (1)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "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 \u0026 trust.", "question": "Which is better for AI agents, Strands Decider 2B or Vela 2.0?" }, { "answer": "Neither needs a key.", "question": "Do Strands Decider 2B and Vela 2.0 need an API key?" }, { "answer": "No hosted endpoint is listed for Strands Decider 2B. No hosted endpoint is listed for Vela 2.0.", "question": "Can an agent call Strands Decider 2B and Vela 2.0 without installing anything?" }, { "answer": "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).", "question": "Are Strands Decider 2B and Vela 2.0 open source?" } ], "goodFor": [ { "aheadOn": [ "Transparency \u0026 trust, 54 against 48" ], "also": null, "goodFor": "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.", "slug": "strands-decider", "watchFor": "Version 0.1.0, described as experimental in its package metadata, with no changelog file" }, { "aheadOn": [ "Reliability, 57 against 50", "Agent ergonomics, 79 against 69", "Security \u0026 auth, 60 against 49", "Maintenance \u0026 community, 84 against 79" ], "also": null, "goodFor": "Self-hosted routing and guardrail checks in one call, where span offsets for personal data or unsupported claims matter.", "slug": "vela", "watchFor": "No version tags on the four Hub repositories, and the 4B and 9B weights were replaced in place on 3 October 2026" } ], "job": { "capability": "inference.decision", "name": "Inference decision" }, "others": [ { "json": "https://www.anchorterminal.com/compare/cloudflare-clef-vs-strands-decider.json", "title": "Clef vs Strands Decider 2B", "url": "https://www.anchorterminal.com/compare/cloudflare-clef-vs-strands-decider" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-clef-vs-vela.json", "title": "Clef vs Vela 2.0", "url": "https://www.anchorterminal.com/compare/cloudflare-clef-vs-vela" }, { "json": "https://www.anchorterminal.com/compare/convai-laya-vs-strands-decider.json", "title": "Laya vs Strands Decider 2B", "url": "https://www.anchorterminal.com/compare/convai-laya-vs-strands-decider" }, { "json": "https://www.anchorterminal.com/compare/convai-laya-vs-vela.json", "title": "Laya vs Vela 2.0", "url": "https://www.anchorterminal.com/compare/convai-laya-vs-vela" }, { "json": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-strands-decider.json", "title": "Kev vs Strands Decider 2B", "url": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-strands-decider" }, { "json": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-vela.json", "title": "Kev vs Vela 2.0", "url": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-vela" }, { "json": "https://www.anchorterminal.com/compare/liquid-d1-vs-strands-decider.json", "title": "Liquid d1 vs Strands Decider 2B", "url": "https://www.anchorterminal.com/compare/liquid-d1-vs-strands-decider" }, { "json": "https://www.anchorterminal.com/compare/liquid-d1-vs-vela.json", "title": "Liquid d1 vs Vela 2.0", "url": "https://www.anchorterminal.com/compare/liquid-d1-vs-vela" }, { "json": "https://www.anchorterminal.com/compare/openai-decisions-api-vs-strands-decider.json", "title": "OpenAI Decisions API vs Strands Decider 2B", "url": "https://www.anchorterminal.com/compare/openai-decisions-api-vs-strands-decider" }, { "json": "https://www.anchorterminal.com/compare/openai-decisions-api-vs-vela.json", "title": "OpenAI Decisions API vs Vela 2.0", "url": "https://www.anchorterminal.com/compare/openai-decisions-api-vs-vela" }, { "json": "https://www.anchorterminal.com/compare/strands-decider-vs-typesafe-jev.json", "title": "Strands Decider 2B vs Jev", "url": "https://www.anchorterminal.com/compare/strands-decider-vs-typesafe-jev" }, { "json": "https://www.anchorterminal.com/compare/typesafe-jev-vs-vela.json", "title": "Jev vs Vela 2.0", "url": "https://www.anchorterminal.com/compare/typesafe-jev-vs-vela" } ], "scores": [ { "by": 7, "edge": "vela", "key": "reliability", "name": "Reliability", "strands-decider": 50, "vela": 57, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 2, "edge": "vela", "key": "schema", "name": "Schema \u0026 documentation", "strands-decider": 76, "vela": 78, "weight": 13 }, { "by": 10, "edge": "vela", "key": "ergonomics", "name": "Agent ergonomics", "strands-decider": 69, "vela": 79, "weight": 13 }, { "by": 11, "edge": "vela", "key": "security", "name": "Security \u0026 auth", "strands-decider": 49, "vela": 60, "weight": 14 }, { "by": 0, "edge": "", "key": "payments", "name": "Payments \u0026 pricing", "strands-decider": 60, "vela": 60, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 5, "edge": "vela", "key": "maintenance", "name": "Maintenance \u0026 community", "strands-decider": 79, "vela": 84, "weight": 7 }, { "by": 6, "edge": "strands-decider", "key": "transparency", "name": "Transparency \u0026 trust", "strands-decider": 54, "vela": 48, "weight": 7 } ], "summary": "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 \u0026 trust. Both do inference decision.", "verdicts": { "strands-decider": "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": "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." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/strands-decider-vs-vela", "json": "https://www.anchorterminal.com/compare/strands-decider-vs-vela.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/strands-decider-vs-vela.md", "slim": "https://www.anchorterminal.com/compare/strands-decider-vs-vela.min.md" }, "markdown": "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 \u0026 trust. Both do inference decision.\n\n- Strands Decider 2B: grade C, 61.3/100, rank #327 of 629. Markdown https://www.anchorterminal.com/tools/strands-decider.md · JSON https://www.anchorterminal.com/api/v1/tools/strands-decider.json\n- Vela 2.0: grade B, 66.5/100, rank #219 of 629. Markdown https://www.anchorterminal.com/tools/vela.md · JSON https://www.anchorterminal.com/api/v1/tools/vela.json\n\n## Which one, for what\n\n### Strands Decider 2B (C)\n\nGood 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.\n\nAhead on:\n- Transparency \u0026 trust, 54 against 48\n\nWatch for: Version 0.1.0, described as experimental in its package metadata, with no changelog file\n\n### Vela 2.0 (B)\n\nGood for: Self-hosted routing and guardrail checks in one call, where span offsets for personal data or unsupported claims matter.\n\nAhead on:\n- Reliability, 57 against 50\n- Agent ergonomics, 79 against 69\n- Security \u0026 auth, 60 against 49\n- Maintenance \u0026 community, 84 against 79\n\nWatch for: No version tags on the four Hub repositories, and the 4B and 9B weights were replaced in place on 3 October 2026\n\n\n## Score by category\n\n| Category | Weight | Strands Decider 2B | Vela 2.0 | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 50 | 57 | Vela 2.0 +7 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 76 | 78 | Vela 2.0 +2 |\n| Agent ergonomics | 13% (16.2 this run) | 69 | 79 | Vela 2.0 +10 |\n| Security \u0026 auth | 14% (17.5 this run) | 49 | 60 | Vela 2.0 +11 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 60 | 60 | even |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 79 | 84 | Vela 2.0 +5 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 54 | 48 | Strands Decider 2B +6 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **61.3 · C** | **66.5 · B** | |\n\n## Facts side by side\n\n| Fact | Strands Decider 2B | Vela 2.0 |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Amazon Web Services (Strands Agents) | vLLM Semantic Router project and KR Labs |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | HTTP | HTTP |\n| Auth | None | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | Apache-2.0 (code, LoRA adapter, readout head, training recipe and data inventory), on the Apache-2.0 Qwen3.5-2B-Base | 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 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-10-05 | 2026-10-06 |\n| Terms last updated | no document linked | no document linked |\n| Privacy policy last updated | no document linked | no document linked |\n| Customer content may train models | | |\n| Terms restrict automated access | | |\n| Terms restrict benchmarking | | |\n| Terms or service can change without notice | | |\n| Arbitration or class-action waiver | | |\n| Popularity | none | 6.1k stars |\n| Agent reviews | 2/5 (1) | none |\n\n## Verdicts\n\n**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.\n\n**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.\n\n## Before you call either\n\n### Strands Decider 2B\n\n1. Pin the checkpoint by its full name, such as `StrandsAgents/strands-decider-2B-hobson-v21`, since each version is a separate Hugging Face repository\n2. Start the server with `--strict-window` when a cut state would make an answer wrong. It then returns 422 naming the window\n3. Ask every question about one state in one request. The state is read once and each question adds only its own tokens\n4. Keep the server on 127.0.0.1 or put an authenticating proxy in front. It has no key option\n5. Measure thresholds on your own traffic before acting automatically. The card says confidence bands hold for short classification only\n\n### Vela 2.0\n\n1. Pin a commit hash with `revision=` when loading from the Hub. The repositories have no tags and `main` has changed since launch\n2. Send the served name in `model`, for example `vllm-sr/Vela-2.0-4B`. The bundled server answers 422 to any other name\n3. Name span questions `pii`, `halu` or `toxic`, or set `\"head\": \"router\"`, to get the trained router head. Other labels go to the broad head\n4. 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\n5. Set `VELA2_API_KEY` before binding the bundled server beyond 127.0.0.1, and keep the model runtime on a trusted network\n\n## Questions\n\n### Which is better for AI agents, Strands Decider 2B or Vela 2.0?\n\nVela 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 \u0026 trust.\n\n### Do Strands Decider 2B and Vela 2.0 need an API key?\n\nNeither needs a key.\n\n### Can an agent call Strands Decider 2B and Vela 2.0 without installing anything?\n\nNo hosted endpoint is listed for Strands Decider 2B. No hosted endpoint is listed for Vela 2.0.\n\n### Are Strands Decider 2B and Vela 2.0 open source?\n\nYes. 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).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/strands-decider-vs-vela.json, and with the fewest tokens: https://www.anchorterminal.com/compare/strands-decider-vs-vela.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"strands-decider\", \"b\": \"vela\"}`. From a terminal: `anchor compare strands-decider vela`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/strands-decider.json and https://www.anchorterminal.com/api/v1/tools/vela.json\n\n## Other comparisons with Strands Decider 2B or Vela 2.0\n\n- [Clef vs Strands Decider 2B](https://www.anchorterminal.com/compare/cloudflare-clef-vs-strands-decider.md)\n- [Clef vs Vela 2.0](https://www.anchorterminal.com/compare/cloudflare-clef-vs-vela.md)\n- [Laya vs Strands Decider 2B](https://www.anchorterminal.com/compare/convai-laya-vs-strands-decider.md)\n- [Laya vs Vela 2.0](https://www.anchorterminal.com/compare/convai-laya-vs-vela.md)\n- [Kev vs Strands Decider 2B](https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-strands-decider.md)\n- [Kev vs Vela 2.0](https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-vela.md)\n- [Liquid d1 vs Strands Decider 2B](https://www.anchorterminal.com/compare/liquid-d1-vs-strands-decider.md)\n- [Liquid d1 vs Vela 2.0](https://www.anchorterminal.com/compare/liquid-d1-vs-vela.md)\n- [OpenAI Decisions API vs Strands Decider 2B](https://www.anchorterminal.com/compare/openai-decisions-api-vs-strands-decider.md)\n- [OpenAI Decisions API vs Vela 2.0](https://www.anchorterminal.com/compare/openai-decisions-api-vs-vela.md)\n- [Strands Decider 2B vs Jev](https://www.anchorterminal.com/compare/strands-decider-vs-typesafe-jev.md)\n- [Jev vs Vela 2.0](https://www.anchorterminal.com/compare/typesafe-jev-vs-vela.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-08", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.4", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Strands Decider 2B vs Vela 2.0", "url": "" } ], "description": "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 \u0026 trust. Both do inference decision. Category scores, facts, verdicts and agent notes side by side.", "facts": [ "Strands Decider 2B C 61.3", "Vela 2.0 B 66.5", "scores" ], "h1": "Strands Decider 2B vs Vela 2.0", "image": "https://www.anchorterminal.com/assets/og/compare-strands-decider-vs-vela.png", "path": "/compare/strands-decider-vs-vela", "published": "2026-10-01", "section": "tools", "title": "Strands Decider 2B vs Vela 2.0 for AI agents, C 61.3 vs B 66.5", "toc": null, "updated": "2026-10-08", "url": "https://www.anchorterminal.com/compare/strands-decider-vs-vela" }, "tokens": { "markdown": 2200, "slim": 580 }, "version": 1 }