Decart vs Fireworks AI
Relationship
Cogito and Fireworks Nexus both serve buyers who need to build on a hosted model API and serve a model in production; larger 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 8 capabilities — Shares model hosting, model inference and model training.
Ludbee capability tags · from the product recordsShared product type — Both ship API service and model API.
Ludbee product recordsLarger scale — Fireworks AI: $17.5B valuation, against Decart's $4B valuation.
Ludbee scale figures · valuation, market cap or revenue estimateAligned comparison
Capability overlap
Shared · 3
Not verified for Fireworks AI · 5
Recorded for Decart. Fireworks AI’s product records say nothing either way — a missing record is not a missing capability.
Not verified for Decart · 2
Recorded for Fireworks 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.
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.
Fireworks AI
API service
Serving for frontier open models and for a customer's own post-trained versions of them, on an inference engine tuned at each layer.
Real-time and batch speech-to-text on Fireworks, aimed at voice workflows that need low-latency transcription at scale.
Training and retraining of custom models on Fireworks, offered across several training surfaces and served on the same platform.
Model API
Drop-in API endpoint that routes each request across models to trade cost against quality.
No counterpart
Decart sells these in a stack layer with no product recorded for Fireworks 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.
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.