Baseten vs Decart
Relationship
Baseten Model APIs and Cogito do comparable work on model hosting; both also serve buyers who need to build on a hosted model API and serve a model in production; smaller scale (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 3 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 recordsSmaller scale — Decart: $4B valuation, against Baseten's $13B valuation.
Ludbee scale figures · valuation, market cap or revenue estimateAligned comparison
Capability overlap
Shared · 3
Not verified for Baseten · 5
Recorded for Decart. Baseten’s product records say nothing either way — a missing record is not a missing capability.
Baseten has no capability Decart lacks, among the 3 recorded here.
Products, side by side
Algorithmic pairing — assembled from recorded fields, not hand-checked
Baseten
API service
Production-grade API launch platform for model labs: takes a lab's model from research to a reliable, scalable, white-labelled API in days, distinct from Baseten's Distribution Platform (model marketplace listing).
Infrastructure service
Named inference runtime (automatic TensorRT/SGLang/vLLM builds, speculative decoding, custom kernel fusion, KV-cache optimisation) that underlies Baseten's Dedicated Inference, Model APIs and Training products.
Model API
Pre-optimised hosted endpoints for open-source frontier models, called without deploying or managing a deployment first.
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.
No counterpart
Baseten sells these in a stack layer with no product recorded for Decart yet — nothing on the other side to compare them against.
Platform
Deploys and serves machine-learning models as production endpoints on managed GPU infrastructure.
Trains and fine-tunes models with reinforcement learning through the Loops SDK, deploying the result onto Baseten's inference stack.
Decart sells these in a stack layer with no product recorded for Baseten 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.