What does kahn1 decide?

It answers 3 kinds of question: choice picks one option from a list you give it; score rates the state on a scale you define; noul returns the probability that a condition holds. Every answer is a typed value with a probability, never free text.

Pull the weights with systemone pull okura66/kahn1 and load them with the runtime named in the manifest.

Can I use kahn1 commercially?

It is published under apache-2.0. Read the licence before shipping; the model card may add terms of its own.

What is kahn1 built on?

Its base model is qwen/qwen3.5-4b, a kahn1 architecture. The Model tree section shows the whole chain.

How much can kahn1 read at once?

The publisher has not recorded a context length. The model has 4.0B parameters.

How accurate is kahn1?

Its publisher reports 72.4% decision accuracy on Kahn1 held-out set (14,663 items: banking intent, sentiment, NLI; the maker's own split). Suites differ between publishers, so compare models on your own labelled examples.

kahn1: open AI decision model by Axel Montzamir (Okura66)

Kahn1-Qwen3.5-4B

Open 4B decision model by Axel Montzamir: reads a text state and answers typed choice, score and noul questions in one forward pass, taking probabilities from the option tokens with permutation debiasing. Apache-2.0 weights; the 3B sibling is research-only.

A personal project. Answers are read from the logits of the option tokens, giving a full distribution and a confidence per answer, with no text generated; permutation debiasing averages over three option orderings. On the maker's own held-out set (banking intent, sentiment and NLI sources) choice reaches 92.3%, score 51.9% exact match and noul 75.5%. The 3B sibling on Qwen2.5-3B is under the Qwen Research License, so it is not commercial and is only linked. Code is MIT, with a site at kahn1.com.

What it decides

choice — picks one option from a set
score — places the input on an ordered scale
noul — answers a yes/no question with one probability

At a glance


Parameters	4B
Base model	`Qwen/Qwen3.5-4B`
Maker	Axel Montzamir (Okura66)
Released	2026-09-25
License	apache-2.0
Reported accuracy	72.4%
Reported latency	88.7 ms p50 / 279.3 ms p95 on an RTX 5070 Ti with vLLM, three orderings

Get the weights

pip install systemonemodels
systemone pull okura66/kahn1

The files are served from the maker's Hugging Face repository, Okura66/Kahn1-Qwen3.5-4B, and verified against the checksums recorded here.

Playground

Build a request for okura66/kahn1. The form and the JSON are the same object; the response panel shows the shape every System One server returns.

Input

StateThe context the questions are asked about. Up to the model's context length.

A yes/no question. The answer is one probability that the condition holds.

Instructions

Response

Placeholder values, in the shape a run returns.

safenoul7%

This model doesn't answer live here. Send this request to your own server for this model; every System One server speaks this shape.

Call it

curl https://api.systemonemodels.ai/v1/systemone \
  -H "Authorization: Bearer $SYSTEMONE_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"model":"okura66/kahn1","state":"Task: clean up inactive accounts before the quarterly report.\nProposed tool call: delete_rows(table=\"customers\", where=\"last_login < 2023-01-01\")\nContext: the customers table is production; there is no backup newer than Friday.","questions":{"safe":{"type":"noul","instructions":"Is this action safe to run without a human approving it first?"}}}'

Decision accuracy	72.4%
Calibration error (ECE)	0.072
Median latency	88.7 ms
p95 latency	279 ms

Axel Montzamir (Okura66): kahn1

Kahn1-Qwen3.5-4B

What it decides

At a glance

Get the weights

Read more

Playground

Axel Montzamir (Okura66): kahn1

Kahn1-Qwen3.5-4B

What it decides

At a glance

Get the weights

Read more

Playground

Providers

Pricing

Performance

Model tree

Activity

Documentation

systemone.yaml

FAQ