Decart vs Dell Technologies
Relationship
Decart Optimization Stack and Dell AI Factory with NVIDIA do comparable work on model training; both also serve buyers who need to run an open-weight model on your own infrastructure, serve a model in production and train or fine-tune a model; larger scale (public).
Assembled from the recorded fields for this pair, not hand-checked. The comparison below is read from each company’s own profile.
3 of 8 capabilities — Shares model hosting, model inference and model training.
Ludbee capability tags · from the product recordsShared product type — Both ship infrastructure service.
Ludbee product recordsLarger scale — Dell Technologies: $360.7B market cap, against Decart's $4B valuation.
Ludbee scale figures · valuation, market cap or revenue estimateAligned comparison
Capability overlap
Shared · 3
Not verified for Dell Technologies · 5
Recorded for Decart. Dell Technologies’s product records say nothing either way — a missing record is not a missing capability.
Not verified for Decart · 4
Recorded for Dell Technologies. Decart’s product records say nothing either way — a missing record is not a missing capability.
Products, side by side
Algorithmic pairing — assembled from recorded fields, not hand-checked
Decart
Infrastructure service
The Decart Optimization Stack (DOS) is Decart's inference and training optimization infrastructure, spanning hardware-aware model design, kernel tooling, proprietary compilers and inference optimization. It is sold to hardware providers and AI teams as engagements covering benchmark optimization, customer-defined kernel and compiler work, cross-workload efficiency gains, and profiler and simulator licensing, and is marketed as hardware-agnostic across GPUs, TPUs, Trainium and AMD accelerators.
Dell Technologies
Infrastructure service
Packaged servers, storage, networking and services sold as one route from AI pilot to production, jointly branded with NVIDIA.
No counterpart
Decart sells these in a stack layer with no product recorded for Dell Technologies yet — nothing on the other side to compare them against.
Application
Delulu is Decart's consumer mobile app for AI photo transformation, published on iOS and Android by Decart.AI, Inc. Its store listing describes it as a way to 'Turn any photo into something fun, weird, or just really good-looking, with a single tap', browsing preset styles and creating stickers to share.
Real-time video editing platform that edits and transforms live video at streaming speed, for enterprises, brands, creators and live/streaming/gaming use cases; built on Decart's DOS infrastructure.
API service
Interactive world model for Physical AI, generating realistic, controllable real-time simulation environments for training autonomous systems, distributed as an API/SDK product built on Decart's Optimization Stack (DOS) infrastructure.
Model API
Cogito is Decart's OpenAI-compatible LLM inference API, serving frontier open-weight models including Kimi K2.6, Kimi K2.7 Code, GLM-5.2, Qwen3 235B and GPT-OSS 120B across Trainium, TPU and GPU capacity. A self-serve Standard tier is billed per token, while an ultra-fast reserved tier advertises 1,000+ tokens per second. It is built on Decart's own DOS optimization stack.
Dell Technologies sells these in a stack layer with no product recorded for Decart yet — nothing on the other side to compare them against.
Developer tool
Curated catalogue of AI models and applications preconfigured with optimised containers for one-click on-premises deployment on Dell hardware, built with Hugging Face.
Data service
Modular data-readiness offering combining Dell storage engines with analytics, processing, orchestration and search engines to prepare enterprise data for AI training and inference.
Hardware
Air-cooled 4U rack server supporting up to eight double-wide PCIe GPUs for flexible AI inference and fine-tuning workloads.
Liquid-cooled 4U rack server with eight NVLink-interconnected NVIDIA HGX B200 GPUs, built for AI inference and model fine-tuning.
Rack-scale server sled pairing NVIDIA Blackwell Ultra GPUs with Grace CPUs over a coherent NVLink memory fabric for large-scale AI training.
Compact workstations built on NVIDIA Grace Blackwell superchips with large unified memory, sold for local large-language-model development and inference.