Jev and Kev compared on the same questions
Source: opper-ai/jev-vs-kev ↗Benchmark code and a 362-question test set that sends each item to Jev and to Kev 4B, and reports accuracy, calibration, latency and cost.
OPEN
Kev decision model
Kev is Jared Palmer's family of open, Jev-compatible models, from 0.8B to 27B parameters. Kev 1.0 pins checkpoints and serving code.
By Jared Palmer · Released 1 Oct 2026
Kev is Jared Palmer's family of open, Jev-compatible decision models, from 0.8B to 27B parameters. A pointer head on a Qwen base scores each option, and the API matches TypeSafe's, so their SDK works against a local Kev server. Kev 1.0, released 1 Oct 2026, pins the family's checkpoints, model cards, evaluation suites and serving code; it introduces no newly trained weights.
Quick answers
What is Kev by Jared Palmer?
How much does Kev cost?
Kev: Published price (vendor-reported): $0.042 per million input tokens and $0 per million output tokens for jaredpalmer/kev-4b on OpenRouter (VENDOR-REPORTED, 2 Nov 2026)
Who makes Kev?
Kev: Jared Palmer
Facts
- Sizes
- 0.8B, 4B, 9B, 27B
- Licence
- Apache-2.0
- Base
- Qwen3.5 (27B: Qwen3.8)
- Release
- Kev 1.0, 1 Oct 2026
- Stars
- 9,758 on GitHub (GitHub API, 2 Nov 2026)
- Price
- $0.042 per million input tokens and $0 per million output tokens for jaredpalmer/kev-4b on OpenRouter (VENDOR-REPORTED, 2 Nov 2026) · Compare prices
- Validated context
- VENDOR-REPORTED: 65,536 tokens for Kev-27B; 8,192 for 0.8B, 4B and 9B, measured on CUAD contracts
Claims and sources
- Kev 1.0's breadth-v1 held-out-dataset test scored a chance-corrected index of 23.3 for 0.8B, 38.0 for 4B, 41.0 for 9B and 52.3 for 27B, against Jev's 54.0, in the maker's fp32 evaluation at shipped temperatures. No Kev trained on these datasets. vendor reportedsource
- Kev-27B's 65,536-token validated context is the longest tested state whose CUAD accuracy stays within three percentage points of its 8k-token accuracy at the 95% lower bound. The smaller models already miss that tolerance at 16k. vendor reportedsource
Links
Source: GitHub → Source: Kev 1.0 release → Source: Hugging Face → Source: Kev 4B on OpenRouter → Source: GitHub API: stars →
Related projects
LinkedIn feed filter
Source: GuitarWag/linkedin-focus-filter ↗A Chrome extension that hides LinkedIn posts that don't match your stated interests, using Kev 0.6B running in the browser on WebGPU. Post text never leaves the browser.
Low Gate lunar-lander benchmark
Source: ErenTerakye/lowgate ↗Decision models choose one of 35 tilt-and-throttle manoeuvres on the same seeded lunar-lander courses. The game waits for the answer, so measured latency never changes the flight score. Across 160 levels per lane, the author reports 159 landings for a scripted autopilot, 156 for Jev, 151 for Kev-27B and 142 for the Laya fine-tune. Prompt selection and Laya training are documented; these results cover this simulator, with recordings available for replay.
Authors' published runs · VENDOR-REPORTED; not independently reproduced
Source: Recorded benchmark → Source: Prompts and training → Source: Licence →
lazycontroller
Source: nicolasambin/lazycontroller ↗An OpenAI-client wrapper that sends closed structured questions to a decision model and falls back on low confidence or unsupported requests. Its saved notebook shows Jev/GPT routing and a local Kev/Ollama path. Shadow mode measures agreement with the slower model; that agreement is not ground-truth accuracy.
Maker's recorded runs · VENDOR-REPORTED; not independently reproduced