kame
kame (SakanaAI, 2026) is an chat model. kame is an open-weights chat model.
by SakanaAI
Best for
- low-latency chat and routing
- request routing and triage
- text classification
Ways to use kame in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your SakanaAI API key. osFoundry discovers kame automatically — assign it to a Maestro role (router, direct, orchestrator, or fallback) in the Pipeline tab and it is live in every chat. Your key, your provider account — no token markup.
Deploy a dedicated endpoint
kame is open-weights — run it locally for free, or deploy a dedicated GPU endpoint in your workspace for reserved capacity with no rate limits.
Use it in a Room App
Room Apps declare AI features in their manifest, then call them with invokeAI:
import { invokeAI } from '@osfoundry/app-sdk'
// 'summarize' is an AI feature declared in your app manifest.
const result = await invokeAI('summarize', userText)
Call it from your own apps
Once a model is wired into your workspace you can host it as an API and reach it from your own services, scripts, or CI — outside osFoundry.
kame vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about kame
Is kame free to use?
kame is free to run locally on your own hardware. Hosted access through osFoundry is metered (input Free (local), output Free (local)). You can switch between local and hosted at any time.
Can I use kame commercially?
Commercial use is allowed with conditions. Licence terms not specified — verify the upstream model card before commercial use. Check upstream documentation.
Can I run kame locally?
Yes. kame is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is kame best at?
kame is well-suited to low-latency chat and routing, request routing and triage, text classification.
How do I use kame in osFoundry?
Paste your SakanaAI API key in the key dialog (or deploy the open weights for self-hostable models), assign kame to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by SakanaAI on April 9, 2026. Source: https://huggingface.co/SakanaAI/kame