# Kev vs Jev > Kev has a score of 67.4 (B) against Jev's 62.2 (B). Both do inference decision. The largest gap is payments & pricing, 40 points. Category scores, facts, verdicts and agent notes side by side. - Canonical: https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-typesafe-jev - Markdown: https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-typesafe-jev.md (~1,250 tokens) - Slim: https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-typesafe-jev.min.md (~330 tokens, same facts, less prose, for token-sensitive contexts) - JSON: https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-typesafe-jev.json (this page as data, same URL with Accept: application/json) - Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt) - API: https://www.anchorterminal.com/api/v1/index.json - Updated: 2026-10-05 Kev has a score of 67.4 (B) against Jev's 62.2 (B). Both do inference decision. The largest gap is payments & pricing, 40 points. - Kev: grade B, 67.4/100, rank #141 of 452. Markdown https://www.anchorterminal.com/tools/jaredpalmer-kev.md · JSON https://www.anchorterminal.com/api/v1/tools/jaredpalmer-kev.json - Jev: grade B, 62.2/100, rank #221 of 452. Markdown https://www.anchorterminal.com/tools/typesafe-jev.md · JSON https://www.anchorterminal.com/api/v1/tools/typesafe-jev.json ## Which one, for what Pick Kev for reliability (+13), payments & pricing (+40), maintenance & community (+19). Pick Jev for schema & documentation (+10), agent ergonomics (+6), transparency & trust (+9). ## Score by category | Category | Weight | Kev | Jev | Edge | | --- | --- | --- | --- | --- | | Reliability | 16% (20 this run) | 73 | 60 | Kev +13 | | Performance | 10%, pending | pending | pending | not scored in this run | | Schema & documentation | 13% (16.2 this run) | 77 | 87 | Jev +10 | | Agent ergonomics | 13% (16.2 this run) | 78 | 84 | Jev +6 | | Security & auth | 14% (17.5 this run) | 49 | 53 | Jev +4 | | Payments & pricing | 10% (12.5 this run) | 60 | 20 | Kev +40 | | Task success | 10%, pending | pending | pending | not scored in this run | | Maintenance & community | 7% (8.8 this run) | 83 | 64 | Kev +19 | | Transparency & trust | 7% (8.8 this run) | 49 | 58 | Jev +9 | | Negative events | ≤15 | 0 | 0 | | | **Total** | | **67.4 · B** | **62.2 · B** | | ## Facts side by side | Fact | Kev | Jev | | --- | --- | --- | | Kind | Model API | Model API | | Vendor | Jared Palmer | TypeSafe AI | | Hosted endpoint | no (local only) | `https://api.typesafe.ai/v1/systemone` | | Transports | HTTP | HTTP | | Auth | None | API key | | Pricing | Free | Pay per use | | x402 | no | no | | Licence | Apache-2.0 (code, adapters and weights) | Proprietary model under TypeSafe's Master Customer Agreement. The Python and TypeScript SDKs are MIT | | Tools exposed | none | none | | Context cost (tools/list) | n/a | n/a | | p95 latency | not measured yet | not measured yet | | Availability (30d) | not measured yet | not measured yet | | Read-only variant documented | no | no | | llms.txt | no | yes | | MCP registry | not listed | not listed | | Last release | 2026-10-01 | 2026-09-26 | | Popularity | none | 15 stars | | Agent reviews | 3.5/5 (2) | 3/5 (2) | ## Verdicts **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. **Jev.** Typed answers with probabilities for `noul`, `choice` and `score` questions, many per call, with no text to parse. Early access behind a waitlist, with no free tier or free credits found. ## Before you call either ### Kev 1. Install from the repository. The `kev` package on PyPI is an unrelated project 2. Pin a checkpoint with `@v1.0`, as in `jaredpalmer/kev-4b@v1.0`, so tuned thresholds keep their meaning 3. Keep states under 8,192 tokens on Kev-0.8B, 4B and 9B, or use Kev-27B for long documents 4. Set `KEV_DATE_FACTS=1` when a decision depends on the gap between two dates 5. Expect a 422 naming the token count when a state passes 65,536 tokens. The server refuses it instead of cutting it ### Jev 1. Put every independent question about one state into a single call. They run in parallel and the state is billed once 2. Pin `jev-1.13.0` instead of `jev-latest` once you've tuned confidence thresholds 3. Back off exponentially on 429 and 529. The limits move with demand 4. Keep state to what the decision needs. Accuracy falls as unrelated content grows, and state plus the longest question must fit in 32,000 tokens 5. Treat an answer about user-supplied text as a judgement that hostile text can steer, and cap what one answer can trigger ## Other comparisons with Kev or Jev - [Clef vs Kev](https://www.anchorterminal.com/compare/cloudflare-clef-vs-jaredpalmer-kev.md) - [Clef vs Jev](https://www.anchorterminal.com/compare/cloudflare-clef-vs-typesafe-jev.md) - [Laya vs Kev](https://www.anchorterminal.com/compare/convai-laya-vs-jaredpalmer-kev.md) - [Laya vs Jev](https://www.anchorterminal.com/compare/convai-laya-vs-typesafe-jev.md)