The AI cloud
you build on.
Every model behind one key. Agents that call real tools. The search, storage and serving underneath. Type below to open a chat with it.
Some work needs your actual files
Hanzo Dev opens the repo you are in, makes the change, and runs the tests. It is in the macOS app.
What is in the cloud
The pieces an AI application needs, already wired to each other and reached with the same key
The model catalog
The Zen family we train ourselves, and frontier models from elsewhere. Change the model name in the request; nothing else changes.
Agents
A Python SDK where an agent is a model, instructions and tools. Put several behind a router when one prompt stops being enough.
Inference
Batching and caching happen on our side. You send a request and read a stream back; the throughput work is not yours to do.
Vectors
Embeddings stored and indexed where the rest of your data already is, so retrieval is a query rather than a second service to run.
Evals
Run a set of cases against a model, keep the results, and compare them after you change the prompt — the only way to know a change helped.
What every call did
Model, latency, tokens and cost per request, per key. A bill that surprises you is a bill you could not see coming.
Guardrails
zen3-guard classifies content before or after a turn. Scope which tools an agent may reach, and keep code execution inside a sandbox.
Load
The same endpoint answers one request a day and a sustained burst. Set a rate limit per key so one client cannot spend another one's headroom.
SDKs
Python, TypeScript, Go and Rust clients, plus a plain HTTP API for everything else. Same endpoints, same request shape.
Your own weights
Bring a model you trained and serve it behind the same API, with the same keys, limits and cost reporting as everything else in the catalog.
Fine-tuning
Start from an open-weight Zen model, train on your data, and get back a model name you can call like any other.
One API, one key
These are separate products elsewhere, each with its own account, its own key and its own bill. Here they are one endpoint that already knows who you are
Models
The Zen family and frontier models from elsewhere, all reached by name at the same endpoint
Vectors
Embedding storage and indexing, so retrieval sits next to your data instead of in a service beside it
Documents
Upload a PDF or a folder of text, get it chunked and indexed, and ask questions across all of it
Search
Keyword and meaning in one query, merged by rank, so an exact product code and a vague description both land
Agents
A model, instructions, and tools it may call — one agent, or several behind a router that picks
Code models
zen5-coder reads a million tokens of context, which is most repositories, so it answers about the code as it is
Workflows
Steps that branch, run in parallel, or loop — for work whose order matters and that a prompt cannot express
Cost and latency
Per call, per key, per model. Where the money went, and which request was slow
Keys and secrets
Sign in through Hanzo IAM, keep credentials in Hanzo KMS, and scope every key to what it is allowed to reach
Chat
A chat surface you can open, embed, or self-host — with threads, streaming, and tools already attached
Prompts
Keep versions, run them against cases, and see which one you actually shipped
Where it runs
Our regions, your cluster, or your laptop. Open weights mean the third option is real
AI Engineering Platform
Build, deploy, and scale AI applications with an integrated suite of tools designed for modern engineering teams.
AI Model Registry
Model Integration
Integrate with OpenAI, Hugging Face, and other machine learning platforms. Deploy and serve custom ML models with built-in scaling and monitoring.
- •One-click API connections to popular ML services
- •Simple deployment of custom models with containerization
- •Performance optimization for inference workloads
Vector Search
High-performance vector database capabilities for semantic search, RAG applications, and similarity matching across billions of vectors.
- •Advanced indexing for fast k-NN and ANN queries
- •Built-in embeddings generation from text and images
- •Hybrid search combining vector and traditional queries
Data Processing
Specialized data processing pipelines for cleaning, transforming, and enriching training data for machine learning models.
- •Automated ETL workflows for AI data preparation
- •Data versioning and lineage tracking
- •Scalable batch and stream processing
AI-Enhanced Features
Ready-to-use AI capabilities that can be integrated into applications with minimal configuration.
- •Content generation and summarization
- •Image and video analysis with computer vision
- •Real-time anomaly detection and predictive analytics
Unified Model Access
Access thousands of AI models through a single, unified API with consistent interfaces and predictable pricing
Zen — open weights from Zoo Labs Foundation
Language, code, vision, image, audio, speech and retrieval, built by Zoo Labs Foundation and served on the Hanzo API. Most have their weights published, so you can serve them yourself
Zen5
Our current frontier model, trained for agent work, reasoning step by step by default.
via Zoo Labs Foundation
- 1M+ context window
- Agentic-trained
- MoDE + CoT
- Preview
Zen5 Pro
High-throughput agentic model for demanding production workloads.
via Zoo Labs Foundation
- 512K context window
- Agentic-trained
- Production optimized
- Preview
Zen5 Max
Maximum context agentic model for document-scale analysis.
via Zoo Labs Foundation
- 2M context window
- Extended CoT
- Document-scale
- Preview
Zen5 Ultra
Deepest reasoning model with multi-pass chain-of-thought.
via Zoo Labs Foundation
- 1M context window
- Deep CoT
- Self-verification
- Preview
Zen5 Mini
Efficient agentic model with zen5-class intelligence.
via Zoo Labs Foundation
- 256K context window
- Agentic-trained
- Cost efficient
- Preview
Zen4
Flagship model for complex reasoning and multi-domain tasks.
via Zoo Labs Foundation
- 744B MoE (40B active)
- 202K context window
- Ultra Max tier
- $3 / $9.60 per MTok
Zen4 Ultra
Maximum reasoning with extended chain-of-thought.
via Zoo Labs Foundation
- 744B MoE (40B active) + CoT
- 262K context window
- Ultra Max tier
- Deep reasoning
Zen4 Pro
High-capability model with efficient MoE architecture.
via Zoo Labs Foundation
- 80B MoE (3B active)
- 131K context window
- Ultra tier
- Efficient MoE
Zen4 Max
Most capable model for complex reasoning and agentic tasks.
via Zoo Labs Foundation
- Dense architecture
- 1M context window
- Ultra Max tier
- Agentic coding
Zen4.6
Extended context for long-document analysis and agentic workflows.
via Zoo Labs Foundation
- Dense architecture
- 1M context window
- Ultra tier
- Cost efficient
Zen4 Mini
Ultra-fast lightweight model, ideal for free tier.
via Zoo Labs Foundation
- Dense architecture
- 128K context window
- Starter tier
- Free tier
Zen4 Thinking
Dedicated reasoning with explicit chain-of-thought.
via Zoo Labs Foundation
- 80B MoE (3B active) + CoT
- 131K context window
- Pro Max tier
- Chain-of-thought
Zen4 Coder
Code-specialized MoE for generation, review, and debugging.
via Zoo Labs Foundation
- 480B MoE (35B active)
- 163K context window
- Ultra tier
- Code generation
Zen4 Coder Pro
Full-precision BF16 code model for complex codebases.
via Zoo Labs Foundation
- 480B Dense BF16
- 131K context window
- Ultra Max tier
- Full-precision
Zen4 Coder Flash
Lightweight code model for speed and inline completions.
via Zoo Labs Foundation
- 30B MoE (3B active)
- 262K context window
- Pro Max tier
- Fast completions
Zen3 Omni
Multimodal model supporting text, vision, audio, and structured output.
via Zoo Labs Foundation
- ~200B Dense Multimodal
- 202K context window
- Pro Max tier
- Text + Vision + Audio
Zen3 VL
Vision-language model for image understanding and visual reasoning.
via Zoo Labs Foundation
- 30B MoE (3B active)
- 262K context window
- Pro Max tier
- Image understanding
Zen3 Nano
Ultra-lightweight model for edge deployment.
via Zoo Labs Foundation
- 8B Dense
- 128K context window
- Starter tier
- Free tier
Zen3 Guard
Content safety classifier for moderation and guardrails.
via Zoo Labs Foundation
- 4B Dense
- 65K context window
- Pro tier
- 119 languages
Zen3 Image
Best general-purpose image generation.
via Zoo Labs Foundation
- Diffusion
- Text-to-image
- Image editing
- $0.04/image
Zen3 Image Max
Maximum quality image generation.
via Zoo Labs Foundation
- Diffusion
- Maximum quality
- Professional creative
- $0.08/image
Zen3 Image Dev
Development model for experimentation.
via Zoo Labs Foundation
- Diffusion
- Development
- Iteration
- $0.0005/step
Zen3 Image Fast
Fastest image model for real-time generation.
via Zoo Labs Foundation
- Diffusion
- Ultra-fast
- Real-time
- $0.00035/step
Zen3 Image SDXL
High-resolution image generation at 1024px.
via Zoo Labs Foundation
- Diffusion
- 1024px
- High-resolution
Zen3 Image Playground
Aesthetic model for artistic generation.
via Zoo Labs Foundation
- Diffusion
- Aesthetic
- Artistic
Zen3 Image SSD
Fastest diffusion model for real-time generation.
via Zoo Labs Foundation
- 1B Diffusion
- Fastest
- Real-time
Zen3 Image JP
Japanese-specialized image generation.
via Zoo Labs Foundation
- Diffusion
- Japanese
- Specialized
Zen3 Audio
Best quality speech-to-text transcription.
via Zoo Labs Foundation
- 1.5B ASR
- 100+ languages
- Best accuracy
Zen3 Audio Fast
Fastest speech-to-text for high-throughput.
via Zoo Labs Foundation
- 809M ASR
- Fastest
- Batch optimized
Zen3 ASR
Real-time streaming speech recognition.
via Zoo Labs Foundation
- Streaming ASR
- Real-time
- Sub-500ms latency
Zen3 ASR v1
First-generation streaming ASR.
via Zoo Labs Foundation
- Streaming ASR
- Legacy
- Compatible
Zen3 TTS
High-quality text-to-speech with natural prosody.
via Zoo Labs Foundation
- 82M TTS
- 40+ voices
- 8 languages
Zen3 TTS HD
Maximum fidelity text-to-speech.
via Zoo Labs Foundation
- TTS HD
- Broadcast-grade
- 48kHz output
Zen3 TTS Fast
Low-latency TTS for real-time voice agents.
via Zoo Labs Foundation
- 82M TTS
- Low latency
- Voice agents
Zen3 Embedding
High-quality text embeddings for RAG and search.
via Zoo Labs Foundation
- 3072 dimensions
- 8K context window
- Pro Max tier
Zen3 Embedding Medium
Balanced embedding model for retrieval.
via Zoo Labs Foundation
- 4B parameters
- 40K context window
- Cost-effective
Zen3 Embedding Small
Lightweight embedding for high throughput.
via Zoo Labs Foundation
- 0.6B parameters
- 32K context window
- High-throughput
Zen3 Embedding OpenAI
OpenAI-compatible embedding endpoint.
via Zoo Labs Foundation
- 3072 dimensions
- 8K context window
- OpenAI compatible
Zen3 Reranker
High-quality reranker for RAG pipelines.
via Zoo Labs Foundation
- 8B parameters
- 40K context window
- RAG accuracy
Zen3 Reranker Medium
Balanced reranker for retrieval.
via Zoo Labs Foundation
- 4B parameters
- 40K context window
- Cost-effective
Zen3 Reranker Small
Lightweight reranker for high throughput.
via Zoo Labs Foundation
- 0.6B parameters
- 40K context window
- Minimal cost
Models from other labs
Same endpoint, same key, same request shape. Reaching for one of these is changing a string, not a migration
Claude Opus 4.6
Anthropic's top tier, for the questions where depth beats speed.
via Anthropic
- 1M context window
- Complex reasoning
- Extended thinking
Claude Sonnet 4.6
Ideal balance of capability and speed for production workloads.
via Anthropic
- 1M context window
- Best balance of speed and intelligence
- Strong coding
- Fast inference
Claude Haiku 4.5
Fastest and most affordable Claude model for high-throughput tasks.
via Anthropic
- 200K context window
- Fastest Anthropic model
- Cost efficient
- Low latency
GPT-4o
OpenAI's flagship model with advanced reasoning capabilities.
via OpenAI
- 128K context window
- Multimodal
- Advanced reasoning
- Tool use
GPT-4o Mini
Cost-efficient OpenAI model for everyday tasks.
via OpenAI
- 128K context window
- Fast and affordable
- Good quality
- Low latency
Gemini 3.1 Pro
Google's flagship with the longest context window.
via Google
- 1M context window
- Multimodal
- Long-context reasoning
- Code generation
GLM-5.2
The newest GLM on the gateway. Reach for it the way you reach for any other model here — change the string.
via Z.ai
- Agentic tool use
- Strong coding
- Served as z-ai/glm-5.2
GLM-4.7
The previous GLM generation, still a common default for high-volume work.
via Z.ai
- Cost efficient
- High throughput
- Served as z-ai/glm-4.7
Custom Models
Deploy and customize models to meet your specific needs
Fine-tuned Models
via Custom
- Domain adaptation
- Company knowledge base
- Specialized tasks
- Improved performance
Hugging Face Models
via Custom
- Community models
- Thousands of options
- Specialized capabilities
- Open source
Custom Embedding Models
via Custom
- Domain-specific embeddings
- Custom similarity metrics
- Enhanced search
- Optimized retrieval
All of it at one address
Routing, documents, vectors and knowledge bases answer at api.hanzo.ai with the key you already have
Routing
Ask for auto and Enso classifies the turn, prices it, and picks — so an easy question does not pay frontier ratesDocuments
Parsing and chunking happen here, so a PDF becomes searchable text without a pipeline you maintainVectors
Embeddings stored and indexed next to your data, so retrieval is a query rather than a second service to runKnowledge bases
Group documents into a base, point a model at it by name, and every answer carries the passages it came fromWhat people build with it
Six shapes that keep coming back, and the models each one reaches for
Support that reads your docs
An assistant grounded in your own content, answering from what you published rather than from what it half-remembers.
Text, images, audio, video
zen-image draws, zen-voice speaks, zen-music composes, zen-video moves. Same key, same billing, one request each.
Search over your own data
Index what you have, then answer questions from it with the passages that support the answer attached.
Work that runs without you
An agent with tools, a trigger, and a place to write the result. Triage a queue, reconcile a ledger, file the report.
Coding agents
Hanzo Dev in the terminal, the MCP tool surface underneath it, and a code model that fits the whole repository in context.
Speech both directions
zen3-asr transcribes thirty languages and can stream while someone is still talking. zen3-tts speaks back.
What it looks like
A client, a model name, and a message. The vector store and the agent below use the same client and the same key
Documentation Example
Vector Search
AI Agents
Experiences from Our Community
Hear from engineering teams who are building the next generation of AI-powered applications
"Hanzo has transformed our approach to electric motorcycle development. Their platform gives us the tools to innovate at a pace that would be impossible with traditional infrastructure."
"Working with Hanzo has transformed our ability to create the highest successfully funded Indiegogo project in history. Their DX platform streamlines our development processes while maintaining the highest standards of quality and safety."
"As a company focused on women's health technology, we need partners who understand both tech and human needs. Hanzo has been instrumental in helping us scale our infrastructure while maintaining the personal touch our customers expect."
The AI Engineering Community
Build with the engineers shipping production AI. Share experiences, get support, and collaborate on best practices.
Make the first call
Create an account, take a key, and send one request. Everything on this page answers at the same endpoint with that key
Documentation
Every endpoint, every parameter, and the SDK method that calls it, in four languages.
Quickstart
A key, a curl, and a response — then the same thing again from a real project you can clone.
Still deciding?
An account is free, and some models cost nothing to call. Try it before you talk to anyone.