{ "data": { "a": { "slug": "jaredpalmer-kev", "name": "Kev", "vendor": "Jared Palmer", "vendorUrl": "https://github.com/jaredpalmer", "kind": "model", "category": "decision-models", "summary": "Kev is a family of four open-weight decision models by Jared Palmer, released together as Kev 1.0 on 1 October 2026 under Apache-2.0.", "url": "https://www.anchorterminal.com/tools/jaredpalmer-kev", "markdownUrl": "https://www.anchorterminal.com/tools/jaredpalmer-kev.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/jaredpalmer-kev.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/jaredpalmer-kev.json", "repo": "https://github.com/jaredpalmer/kev", "license": "Apache-2.0 (code, adapters and weights)", "transports": [ "http" ], "packages": [], "auth": "none", "authNotes": "No account. `kev.serve` binds to 127.0.0.1 and is open by default. Setting `KEV_API_KEY` makes it require `Authorization: Bearer \u003ckey\u003e` on `/v1/*`, which the TypeSafe clients always send. The weights download from Hugging Face without an account.", "pricing": "free", "pricingNotes": "Free and open source, with nothing to buy. You pay for the hardware. The Modal deploy skill lists $0.80 an hour for Kev-0.8B on an L4, $1.95 for Kev-4B on an L40S, $3.95 for Kev-9B on an H100 and $6.25 for Kev-27B on a B200 while a container is up, scaling to zero after five idle minutes (https://github.com/jaredpalmer/kev/blob/main/skills/kev-deploy/SKILL.md). Those are Modal's GPU rates as the skill records them, not a Kev price.", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402. Kev is software you run, and its server has no payment route (checked 2026-10-02).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-02" }, "docsUrl": "https://github.com/jaredpalmer/kev#readme", "capabilities": [ "inference.decision" ], "tags": [ "model", "open-source", "open-weights", "self-hosted", "local", "free", "python" ], "lastRelease": "2026-10-01", "graded": true, "anchor": { "graded": true, "score": 67.4, "grade": "B", "agentReady": false, "rank": 140, "ranked": true, "rankOf": 460, "categoryRank": 2, "methodology": "0.3", "run": "2026-10-01", "scores": { "ergonomics": 78, "maintenance": 83, "payments": 60, "reliability": 73, "schema": 77, "security": 49, "transparency": 49 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-01" }, "negative": 0, "verdict": "Apache-2.0 code, adapters and heads on Apache-2.0 Qwen bases, with release tarballs and SHA-256 checksums for the 0.8B, 4B and 9B models. No package. `pip install kev` installs an unrelated 2021 ORM, so Kev runs from a Git clone with uv.", "bestFor": "Self-hosted classification, routing, triage and rubric scoring where a probability matters, especially for teams already calling Jev who want the same API on their own hardware.", "strengths": [ "Apache-2.0 code, adapters and heads on Apache-2.0 Qwen bases, with release tarballs and SHA-256 checksums for the 0.8B, 4B and 9B models", "The same `/v1/systemone` request and answer shapes as Jev, and the README says TypeSafe's Python SDK works against it unchanged", "A fitted temperature per checkpoint, with Brier scores, calibration error and confident-error rates published for each model", "Runs on CUDA, ROCm and Apple Silicon, from a 4 GB GPU for Kev-0.8B to one 80 GB GPU for Kev-27B, and deploys to Modal with one command", "Release notes that list known failures with numbers, such as date arithmetic and Kev-0.8B's tool-routing accuracy" ], "weaknesses": [ "No package. `pip install kev` installs an unrelated 2021 ORM, so Kev runs from a Git clone with uv", "Kev-0.8B, 4B and 9B are validated to 8,192 tokens of state, though the server accepts 65,536", "Jared Palmer wrote 312 of the 333 commits we cloned", "No SECURITY.md, disclosure policy or advisories, and the server is open unless `KEV_API_KEY` is set", "Below 27B it trails Jev on knowledge questions and date arithmetic, with MMLU-Pro at 0.59 for Kev-9B against Jev's 0.84" ], "agentNotes": [ "Install from the repository. The `kev` package on PyPI is an unrelated project", "Pin a checkpoint with `@v1.0`, as in `jaredpalmer/kev-4b@v1.0`, so tuned thresholds keep their meaning", "Keep states under 8,192 tokens on Kev-0.8B, 4B and 9B, or use Kev-27B for long documents", "Set `KEV_DATE_FACTS=1` when a decision depends on the gap between two dates", "Expect a 422 naming the token count when a state passes 65,536 tokens. The server refuses it instead of cutting it" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 2, "avgRating": 3.5, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.3", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 67.4 } ], "editorialScores": { "ergonomics": 78, "maintenance": 83, "payments": 60, "reliability": 73, "schema": 77, "security": 49, "transparency": 70 }, "provenanceScore": 27 }, "connect": { "install": "git clone https://github.com/jaredpalmer/kev.git \u0026\u0026 cd kev \u0026\u0026 uv sync --extra serve\nuv run --extra serve python -m kev.serve --run jaredpalmer/kev-4b@v1.0 --port 8009", "http": "curl -s localhost:8009/v1/systemone -H 'content-type: application/json' \\\n -d '{\"model\":\"kev-latest\",\"state\":\"Checkout has failed for every customer for an hour.\",\"questions\":{\"urgent\":{\"type\":\"noul\",\"instructions\":\"Is this request urgent?\"},\"team\":{\"type\":\"choice\",\"criteria\":{\"billing\":\"Payments and refunds\",\"technical\":\"Outages and errors\"}}}}'" }, "letme": { "capability": "https://letme.dev/inference.decision", "tool": "https://letme.dev/jaredpalmer-kev" }, "area": "models", "provenance": { "legalEntity": "", "domain": "github.com/jaredpalmer", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://github.com/jaredpalmer/kev/releases", "securityTxt": "none", "checked": "2026-10-01", "notes": [ "An individual's open-source project under Apache-2.0, with no company named in the licence, README or package metadata. The pyproject names Jared Palmer as author.", "No vendor domain. The code is at github.com/jaredpalmer/kev and the weights at huggingface.co/jaredpalmer, so the domain line names the GitHub account and scores no domain age.", "Software you run, so there's no hosted endpoint, terms or privacy policy to check.", "The changelog is the GitHub releases page (`kev-1.0`, 1 October 2026) and docs/releases/kev-1.0.md." ], "score": 27 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/jaredpalmer-kev.json", "live": { "slug": "jaredpalmer-kev", "versions": [ { "registry": "github", "name": "jaredpalmer/kev", "version": "kev-1.0", "released": "2026-10-01", "seenAt": "2026-10-05T16:55:54.816853197Z" } ], "githubStars": 8494, "domain": { "domain": "github.com/jaredpalmer", "checkedAt": "2026-10-04T13:10:21.931207592Z" }, "updatedAt": "2026-10-05T16:55:54.816853197Z" } }, "answer": "Kev scores 67.4 (B) on agent readiness against Strands Decider 2B's 61.3 (C), and leads in 4 of 7 scored categories. Strands Decider 2B leads on transparency \u0026 trust.", "b": { "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": 235, "ranked": true, "rankOf": 460, "categoryRank": 5, "methodology": "0.3", "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": "0.3", "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" }, "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Jared Palmer", "b": "Amazon Web Services (Strands Agents)", "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, adapters and weights)", "b": "Apache-2.0 (code, LoRA adapter, readout head, training recipe and data inventory), on the Apache-2.0 Qwen3.5-2B-Base", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-10-01", "b": "2026-10-05", "name": "Last release" }, { "a": "3.5/5 (2)", "b": "2/5 (1)", "name": "Agent reviews" } ], "faq": [ { "answer": "Kev scores 67.4 (B) on agent readiness against Strands Decider 2B's 61.3 (C), and leads in 4 of 7 scored categories. Strands Decider 2B leads on transparency \u0026 trust.", "question": "Which is better for AI agents, Kev or Strands Decider 2B?" }, { "answer": "Neither needs a key.", "question": "Do Kev and Strands Decider 2B need an API key?" }, { "answer": "No hosted endpoint is listed for Kev. No hosted endpoint is listed for Strands Decider 2B.", "question": "Can an agent call Kev and Strands Decider 2B without installing anything?" }, { "answer": "Yes. Kev is open source (Apache-2.0 (code, adapters and weights)). 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).", "question": "Are Kev and Strands Decider 2B open source?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 73 against 50", "Agent ergonomics, 78 against 69" ], "also": null, "goodFor": "Self-hosted classification, routing, triage and rubric scoring where a probability matters, especially for teams already calling Jev who want the same API on their own hardware.", "slug": "jaredpalmer-kev", "watchFor": "No package. `pip install kev` installs an unrelated 2021 ORM, so Kev runs from a Git clone with uv" }, { "aheadOn": [ "Transparency \u0026 trust, 54 against 49" ], "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" } ], "job": { "capability": "inference.decision", "name": "Inference decision" }, "others": [ { "json": "https://www.anchorterminal.com/compare/cloudflare-clef-vs-jaredpalmer-kev.json", "title": "Clef vs Kev", "url": "https://www.anchorterminal.com/compare/cloudflare-clef-vs-jaredpalmer-kev" }, { "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/convai-laya-vs-jaredpalmer-kev.json", "title": "Laya vs Kev", "url": "https://www.anchorterminal.com/compare/convai-laya-vs-jaredpalmer-kev" }, { "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/jaredpalmer-kev-vs-typesafe-jev.json", "title": "Kev vs Jev", "url": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-typesafe-jev" }, { "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" } ], "scores": [ { "by": 23, "edge": "jaredpalmer-kev", "jaredpalmer-kev": 73, "key": "reliability", "name": "Reliability", "strands-decider": 50, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 1, "edge": "jaredpalmer-kev", "jaredpalmer-kev": 77, "key": "schema", "name": "Schema \u0026 documentation", "strands-decider": 76, "weight": 13 }, { "by": 9, "edge": "jaredpalmer-kev", "jaredpalmer-kev": 78, "key": "ergonomics", "name": "Agent ergonomics", "strands-decider": 69, "weight": 13 }, { "by": 0, "edge": "", "jaredpalmer-kev": 49, "key": "security", "name": "Security \u0026 auth", "strands-decider": 49, "weight": 14 }, { "by": 0, "edge": "", "jaredpalmer-kev": 60, "key": "payments", "name": "Payments \u0026 pricing", "strands-decider": 60, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 4, "edge": "jaredpalmer-kev", "jaredpalmer-kev": 83, "key": "maintenance", "name": "Maintenance \u0026 community", "strands-decider": 79, "weight": 7 }, { "by": 5, "edge": "strands-decider", "jaredpalmer-kev": 49, "key": "transparency", "name": "Transparency \u0026 trust", "strands-decider": 54, "weight": 7 } ], "summary": "Kev scores 67.4 (B) on agent readiness against Strands Decider 2B's 61.3 (C), and leads in 4 of 7 scored categories. Strands Decider 2B leads on transparency \u0026 trust. Both do inference decision.", "verdicts": { "jaredpalmer-kev": "Apache-2.0 code, adapters and heads on Apache-2.0 Qwen bases, with release tarballs and SHA-256 checksums for the 0.8B, 4B and 9B models. No package. `pip install kev` installs an unrelated 2021 ORM, so Kev runs from a Git clone with uv.", "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." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-strands-decider", "json": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-strands-decider.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-strands-decider.md", "slim": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-strands-decider.min.md" }, "markdown": "Kev scores 67.4 (B) on agent readiness against Strands Decider 2B's 61.3 (C), and leads in 4 of 7 scored categories. Strands Decider 2B leads on transparency \u0026 trust. Both do inference decision.\n\n- Kev: grade B, 67.4/100, rank #140 of 460. Markdown https://www.anchorterminal.com/tools/jaredpalmer-kev.md · JSON https://www.anchorterminal.com/api/v1/tools/jaredpalmer-kev.json\n- Strands Decider 2B: grade C, 61.3/100, rank #235 of 460. Markdown https://www.anchorterminal.com/tools/strands-decider.md · JSON https://www.anchorterminal.com/api/v1/tools/strands-decider.json\n\n## Which one, for what\n\n### Kev (B)\n\nGood for: Self-hosted classification, routing, triage and rubric scoring where a probability matters, especially for teams already calling Jev who want the same API on their own hardware.\n\nAhead on:\n- Reliability, 73 against 50\n- Agent ergonomics, 78 against 69\n\nWatch for: No package. `pip install kev` installs an unrelated 2021 ORM, so Kev runs from a Git clone with uv\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 49\n\nWatch for: Version 0.1.0, described as experimental in its package metadata, with no changelog file\n\n\n## Score by category\n\n| Category | Weight | Kev | Strands Decider 2B | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 73 | 50 | Kev +23 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 77 | 76 | Kev +1 |\n| Agent ergonomics | 13% (16.2 this run) | 78 | 69 | Kev +9 |\n| Security \u0026 auth | 14% (17.5 this run) | 49 | 49 | even |\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) | 83 | 79 | Kev +4 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 49 | 54 | Strands Decider 2B +5 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **67.4 · B** | **61.3 · C** | |\n\n## Facts side by side\n\n| Fact | Kev | Strands Decider 2B |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Jared Palmer | Amazon Web Services (Strands Agents) |\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, adapters and weights) | Apache-2.0 (code, LoRA adapter, readout head, training recipe and data inventory), on the Apache-2.0 Qwen3.5-2B-Base |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-10-01 | 2026-10-05 |\n| Agent reviews | 3.5/5 (2) | 2/5 (1) |\n\n## Verdicts\n\n**Kev.** Apache-2.0 code, adapters and heads on Apache-2.0 Qwen bases, with release tarballs and SHA-256 checksums for the 0.8B, 4B and 9B models. No package. `pip install kev` installs an unrelated 2021 ORM, so Kev runs from a Git clone with uv.\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## Before you call either\n\n### Kev\n\n1. Install from the repository. The `kev` package on PyPI is an unrelated project\n2. Pin a checkpoint with `@v1.0`, as in `jaredpalmer/kev-4b@v1.0`, so tuned thresholds keep their meaning\n3. Keep states under 8,192 tokens on Kev-0.8B, 4B and 9B, or use Kev-27B for long documents\n4. Set `KEV_DATE_FACTS=1` when a decision depends on the gap between two dates\n5. Expect a 422 naming the token count when a state passes 65,536 tokens. The server refuses it instead of cutting it\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## Questions\n\n### Which is better for AI agents, Kev or Strands Decider 2B?\n\nKev scores 67.4 (B) on agent readiness against Strands Decider 2B's 61.3 (C), and leads in 4 of 7 scored categories. Strands Decider 2B leads on transparency \u0026 trust.\n\n### Do Kev and Strands Decider 2B need an API key?\n\nNeither needs a key.\n\n### Can an agent call Kev and Strands Decider 2B without installing anything?\n\nNo hosted endpoint is listed for Kev. No hosted endpoint is listed for Strands Decider 2B.\n\n### Are Kev and Strands Decider 2B open source?\n\nYes. Kev is open source (Apache-2.0 (code, adapters and weights)). 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).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-strands-decider.json, and with the fewest tokens: https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-strands-decider.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"jaredpalmer-kev\", \"b\": \"strands-decider\"}`. From a terminal: `anchor compare jaredpalmer-kev strands-decider`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/jaredpalmer-kev.json and https://www.anchorterminal.com/api/v1/tools/strands-decider.json\n\n## Other comparisons with Kev or Strands Decider 2B\n\n- [Clef vs Kev](https://www.anchorterminal.com/compare/cloudflare-clef-vs-jaredpalmer-kev.md)\n- [Clef vs Strands Decider 2B](https://www.anchorterminal.com/compare/cloudflare-clef-vs-strands-decider.md)\n- [Laya vs Kev](https://www.anchorterminal.com/compare/convai-laya-vs-jaredpalmer-kev.md)\n- [Laya vs Strands Decider 2B](https://www.anchorterminal.com/compare/convai-laya-vs-strands-decider.md)\n- [Kev vs Jev](https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-typesafe-jev.md)\n- [Strands Decider 2B vs Jev](https://www.anchorterminal.com/compare/strands-decider-vs-typesafe-jev.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-06", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.3", "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": "Kev vs Strands Decider 2B", "url": "" } ], "description": "Kev scores 67.4 (B) on agent readiness against Strands Decider 2B's 61.3 (C), and leads in 4 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": [ "Kev B 67.4", "Strands Decider 2B C 61.3", "scores" ], "h1": "Kev vs Strands Decider 2B", "image": "https://www.anchorterminal.com/assets/og/compare-jaredpalmer-kev-vs-strands-decider.png", "path": "/compare/jaredpalmer-kev-vs-strands-decider", "published": "2026-10-01", "section": "tools", "title": "Kev vs Strands Decider 2B for AI agents, B 67.4 vs C 61.3", "toc": null, "updated": "2026-10-06", "url": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-strands-decider" }, "tokens": { "markdown": 1800, "slim": 530 }, "version": 1 }