Decart vs Together AI
Relationship
Cogito and Together Inference both serve buyers who need to build on a hosted model API and serve a model in production; same layer and the same scale band (growth-stage private).
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 API service, infrastructure service and model API.
Ludbee product recordsSame scale band — Both growth-stage private.
Ludbee scale bands · from valuation and funding figuresAligned comparison
Capability overlap
Shared · 3
Not verified for Together AI · 5
Recorded for Decart. Together AI’s product records say nothing either way — a missing record is not a missing capability.
Not verified for Decart · 1
Recorded for Together AI. 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
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.
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.
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.
Together AI
API service
Asynchronous bulk inference for workloads that do not need a real-time response, priced below Together's serverless rate.
A managed service for fine-tuning open-source models on a customer's own data and serving the result on Together's infrastructure.
Infrastructure service
Dedicated, reserved GPU containers for model inference with guaranteed performance, billed per GPU-hour.
Reserved NVIDIA GPU clusters for training and large-scale inference.
Model API
Hosted API serving open-weight text, image and audio models, billed per token.
No counterpart
Decart sells these in a stack layer with no product recorded for Together AI 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.
Together AI sells these in a stack layer with no product recorded for Decart yet — nothing on the other side to compare them against.
Developer tool
Custom model training service covering supervised fine-tuning and direct preference optimization, billed per token.