OctoAI
OctoAI (formerly OctoML) was a Seattle-based AI inference platform founded in 2019 as a University of Washington Allen School spin-out of the Apache TVM project. The company originally focused on machine-learning model optimization and compilation across CPUs, GPUs, and accelerators, and in June 2023 launched a generative-AI SaaS inference platform that served open-source foundation models (Llama 2, Mixtral, SDXL, Stable Diffusion, Whisper) behind OpenAI-style REST APIs with Python and TypeScript SDKs. In January 2024 OctoML formally rebranded to OctoAI and in April 2024 unveiled OctoStack, a self-contained generative-AI production stack for deploying models inside customer VPC and on-premises environments across NVIDIA GPUs, AMD GPUs, and AWS Inferentia. NVIDIA acquired OctoAI in September 2024 for a reported $165M (down from a 2021 peak valuation of ~$900M), with CEO Luis Ceze and key staff joining NVIDIA. OctoAI sent customers a "Wind down of OctoAI Services" notice and terminated all hosted endpoints, accounts, and SDK access on 31 October 2024. The octo.ai domain now 301-redirects to nvidia.com and no public OctoAI product, API, dashboard, or developer portal remains; the technology has been absorbed into NVIDIA's internal AI inference stack and is not separately purchasable. This catalog entry is a historical record of the former OctoAI developer surface and the GitHub artifacts that remain.
Index entry only — little beyond a description and a link, and nothing machine-readable enough for an agent to act on without a human reading the site first.
API Evangelist profiles OctoAI the way a machine reads it — 21 machine-readable artifacts across 5 APIs, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.
Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — OctoAI scores 10.7/100 (minimal), with a separate agent-readiness read of 0/100 (human only). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.
Kin Score
This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance.
Kin Score
How this is scored →scored 2026-07-27 · rubric v0.5
How we profile OctoAI
Each block below is one kind of artifact we hold for OctoAI. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.
APIs 5
Each API is captured as its own OpenAPI definition — every operation, parameter, and response. This is the single most useful machine-readable description of what an API does, and it's what lets us score, lint, mock, and generate against it without asking the provider for anything.
Individual APIs this provider publishes, each with its own machine-readable definition.
OctoAI Text Gen Inference API
OpenAI-compatible chat and text-completion endpoints serving open-source LLMs including Llama 2, Llama 3, Mixtral 8x7B, Mistral 7B, Code Llama, and customer fine-tunes. Supporte...
OctoAI Image Gen Inference API
Text-to-image and image-to-image inference for SDXL, SDXL-Lightning, Stable Diffusion 1.5, and SSD-1B with ControlNet, LoRA, and adapter support, plus inpainting and asset-manag...
OctoAI Asset Library API
Endpoints for uploading, listing, and managing user assets — checkpoints, LoRAs, textual inversions, ControlNets, and VAE files — used by the image and text inference APIs. The ...
OctoAI Compute Service API
Container-deployment API ("Compute Service") that let customers build, register, and serve their own custom model containers on OctoAI's managed GPU fleet, with autoscaling and ...
OctoStack
OctoStack was OctoAI's self-contained generative-AI production stack for deploying open and customer-trained foundation models inside a customer's VPC or on-premises environment...
Features 6
The notable capabilities this provider advertises, captured as structured features so they can be searched and compared instead of read one landing page at a time.
Notable capabilities this provider offers.
OpenAI-Compatible Inference
OctoAI's text and image endpoints implemented OpenAI-style request and response shapes so existing OpenAI client code could be repointed by changing the base URL and API key.
Open-Source Model Catalog
A shared catalog hosted Llama 2/3, Mixtral, Mistral, Code Llama, SDXL, SSD-1B, Stable Diffusion 1.5, and Whisper behind per-token and per-image pricing without GPU provisioning.
Custom Model Compute Service
Customers could package their own model containers and have OctoAI autoscale them on a managed GPU fleet, billed by GPU-second.
Asset Library
Upload and manage LoRAs, checkpoints, textual inversions, VAEs, and ControlNets and apply them at request time to image and text-generation endpoints.
OctoStack Private Deployment
Self-contained inference stack that ran inside a customer VPC or on-premises across NVIDIA, AMD, and AWS Inferentia hardware with fine-tuning, batching, and asset management bui...
TVM-Based Model Optimization
OctoAI's optimization pipeline descended from Apache TVM (created by founder Tianqi Chen) and used ML-guided compilation to improve throughput and latency across heterogeneous a...
Security Posture 1
Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Use Cases 4
What developers actually build with this provider — captured so the catalogue answers 'what is this for', not just 'what does this expose'.
What developers build with this provider.
Repointing OpenAI Workloads to Open Models
Teams used the OpenAI-compatible endpoints to swap GPT-3.5/4 calls for Llama 2 / Mixtral at lower cost without rewriting client code.
Generative Image Pipelines
Product, marketing, and creative teams ran SDXL-based image generation with custom LoRAs and ControlNets for branded asset production.
Private Generative AI in Regulated Industries
Healthcare, financial-services, and government customers deployed OctoStack in-VPC or on-premises to keep prompts, completions, and model weights inside their security boundary.
Custom Fine-Tune Hosting
Teams fine-tuned open-weights models and served the resulting adapters and full-weight checkpoints behind OctoAI inference endpoints without managing GPU infrastructure.
Integrations 5
Pre-built integrations with other platforms tell you where this provider already fits in a stack.
Pre-built integrations with other platforms and tools.
NVIDIA
Acquired OctoAI in September 2024 for a reported $165M; OctoAI team and technology absorbed into NVIDIA's AI inference stack and all OctoAI hosted services terminated on 31 Octo...
Apache TVM
OctoAI's optimization stack originated from Apache TVM, the deep-learning compiler founded by OctoAI co-founder Tianqi Chen at the University of Washington.
AWS
OctoAI was an AWS Partner; OctoStack ran on AWS GPU instances and AWS Inferentia accelerators, with sagemaker-examples published in the GitHub org.
Docker
OctoAI ran a DockerCon 2023 generative-AI workshop and published the dockercon23-octoai workshop repo.
LangChain & LlamaIndex
OctoAI's LLM endpoints shipped with documented LangChain and LlamaIndex providers, demonstrated in the octoml-llm-qa sample repo.
Resources
Every other property we hold for OctoAI — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.
Build 2
SDKs, sample code, and the tooling you integrate with
Access & Security 1
Authentication, authorization, and security posture
Company 3
The organization behind the API
Other 4
Properties that don't map to a standard resource type
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