Votre objectif
Être visible là où l'IA répond
Automatiser les processus
Construire un produit
Déployer des agents IA
Connecter et moderniser vos systèmes
Savoir où nous en sommes
Cas d'Usage
CRMRenforcer les relations clientsPopulaireE-CommerceAugmenter les ventes en ligneSystème de réservationRéservations 24h/24Gestion de projetCoordonner les équipesFacturationÊtre payé plus viteAnalytiqueDécisions basées sur donnéesLocal AI · Recipe · 4× RTX PRO 6000
GLM-5.3-Flash NVFP4 with vLLM on 4× RTX PRO 6000 (with DFlash): 255 tok/s according to github.com (dataset as of Nov 3, 2026).
Every sourced value of this recipe, each with its condition and source. Bars relative to the largest value in the group.
What matters before you rebuild it.
1 request, generation at 32K context (speed table; measured only as a path of four Sparks inside a ring of eight, not as a ring of four), thinking always on (measured before the profile default high, i.e. template default max), with MTP3 (per recipe) Source
1 request, prose prompt, with MTP + DFlash2 (per recipe) Source
Prose decode, 1 request; quality (FP8 KV, 4-bit dense): GSM8K 98.8% / HumanEval 95.7% / HumanEval+ & MBPP+ 86.5% Source
1 request, prose prompt, with MTP + DFlash2 (per recipe) Source
1 request, prose prompt, with DFlash2 (per recipe) Source
1 request, prose prompt, with DFlash2, TR3 weights (per recipe) Source
In a workshop we work out which models and which hardware fit your tasks, and build the first agent on your infrastructure.
