Cómo usa Scaled Cognition Together AI
3–4 months
“3–4 months of cumulative research time recovered”
Tal como se publicó en together.ai. Capturado por usedby el 3 oct 2026.
Qué pasó
Scaled Cognition trains its Large Action Models (APT-1) on Together AI GPU Clusters, using bare-metal B200 and H200 GPUs with direct SSH access to run Slurm and a custom multi-node training stack.
Resumen escrito por usedby a partir de la página de origen, en inglés. Las cifras son de Together AI y de Scaled Cognition, no nuestras.
- ~50%“~50% cost savings vs. other compute providers”
As a result, they recovered an estimated 3–4 months of cumulative research time previously lost to infrastructure failures and achieved ~50% cost savings vs. other providers
We spent 3-4 months blocked by infrastructure failures with previous providers—debugging networking issues that had nothing to do with our models. Together AI's cluster has had zero training-blocking issues since we switched. That reliability, combined with significant cost savings compared to other providers, completely changed our development velocity. But honestly, the responsive support is what keeps us here: shared Slack channel, problems resolved within hours, smooth scaling of our training cluster as our needs have been expanding. Together AI lets us focus on building breakthrough models instead of fighting infrastructure.
Lo que dice la historia, y lo que verificamos
Comparamos la historia con su página en línea el 3 oct 2026.
- La cifra: 3–4 monthsVerificadoImpresa palabra por palabra en la página, cerca del nombre de Scaled Cognition.
- El pasaje citado arribaVerificadoCopiado palabra por palabra de la página, cerca del nombre de Scaled Cognition.
- Los números de nuestro resumenVerificadoCada uno está impreso en la página.
- Scaled Cognition usa Together AIVerificadoLínea de nivel Confirmado. Última verificación entre todas las fuentes: 3 oct 2026.
- El resultado en síNo verificadoLo citamos; no lo medimos.
Más historias
Misma empresa, misma herramienta o mismo sector.
