OpenClaw vs MaxClaw: Self-Hosted vs Cloud AI Agents (2026)

Quick Overview

The debate between self-hosted and cloud AI agents comes down to one fundamental trade-off: control versus convenience. OpenClaw gives you complete control over your agents, your data, and your infrastructure. MaxClaw removes all infrastructure management so you can start running agents in minutes without touching a terminal.

Neither approach is universally better. The right choice depends on your sensitivity to data privacy, how much infrastructure you are willing to manage, what models you need to run, and whether your workloads require deep customization or just fast deployment.

This comparison was triggered by a discussion in the OpenClaw community (6 upvotes, 16 comments on the relevant thread) where developers were actively weighing their options after MiniMax launched MaxClaw. The key concerns raised: data residency, vendor lock-in, cost predictability, and whether MaxClaw's model quality was comparable to what you get when running Claude or GPT-4 through OpenClaw.

What is MaxClaw?

MaxClaw is a cloud-hosted AI agent platform built by MiniMax, a Chinese AI company known for its large multimodal language models. MaxClaw lets you configure AI agents through a web interface or API, then run them on MiniMax's managed infrastructure. You define the agent's role, instructions, and task behaviors; MiniMax handles everything else — hosting, scaling, model serving, and uptime.

MaxClaw agents run on MiniMax's own model lineup, which includes MiniMax-Text-01 for text tasks and multimodal variants for image and audio capabilities. The platform includes built-in tools for web search, document parsing, and image generation. Agents can be connected to external APIs through a webhook-based integration system.

The appeal is straightforward: no servers to configure, no gateway to run, no CLI to learn. You create an agent in the MaxClaw dashboard, define its behavior, and it is live. For teams that want AI agents without any DevOps overhead, that is a compelling proposition.

1. Log in to MaxClaw dashboard (app.maxclaw.ai)
2. Click "Create Agent"
3. Define agent role and instructions in the web form
4. Select a MiniMax model (MiniMax-Text-01, abab6.5s, etc.)
5. Enable built-in tools (web search, document parser, image gen)
6. Set webhook URL for external integrations (optional)
7. Click "Deploy" — agent is live on MiniMax infrastructure

No terminal, no server, no configuration files.
All data flows through MiniMax cloud.

What is OpenClaw?

OpenClaw is an open-source AI agent framework that you run on your own machine or server. Agents are defined using SOUL.md, a markdown configuration file that specifies identity, personality, rules, skills, and communication channels. You register agents with the OpenClaw CLI, start the gateway, and your agents are live — running entirely on infrastructure you control.

OpenClaw supports multiple LLM providers: Anthropic (Claude), OpenAI (GPT-4), Google (Gemini), and Ollama for local open-weight models. Built-in channel integrations for Telegram, Slack, Discord, and Email are enabled with a single line in the SOUL.md file. Multi-agent teams are coordinated through an agents.md file with natural language @mention routing.

# 1. Create SOUL.md on your machine
cat > agents/analyst/SOUL.md << 'EOF'
# Data Analyst

## Identity
- Name: Analyst
- Role: Data Research Analyst
- Model: claude-opus-4-6

## Personality
- Methodical and detail-oriented
- Presents data with clear context and actionable insight

## Rules
- Always cite sources and include confidence levels
- Flag data that is older than 6 months
- Summarize key findings before detailed breakdown

## Skills
- browser: Search the web for research data
- files: Read and process local data files

## Channels
- telegram: true
EOF

# 2. Register and run — entirely on your infrastructure
openclaw agents add analyst --workspace ./agents/analyst
openclaw gateway start

The critical difference: your data never leaves your machine unless you choose to send it to a cloud LLM provider. The gateway, agent logic, and session data all stay local. If you use Ollama for the model layer, the entire stack is air-gapped.

The Core Differences That Actually Matter

Data Privacy and Residency

This is the most significant difference. With OpenClaw self-hosted, your agent prompts, task data, memory files, and conversation history stay on your machine or your private server. You control where data lives and who can access it. If you add Ollama to the stack, no data leaves your network at all.

With MaxClaw, everything passes through MiniMax's infrastructure. Your agent instructions, the data you send agents to process, and all outputs are processed on MiniMax servers. MiniMax is a Chinese company, which means different data protection regulations apply compared to US or EU-based cloud providers. For teams handling customer data, proprietary research, or legally regulated information (HIPAA, GDPR, SOC 2), this matters enormously.

Model Choice and Quality

MaxClaw is tied to MiniMax's model lineup. MiniMax models are capable — particularly for Chinese-language tasks and multimodal workflows — but they are not the leading models for English-language reasoning, code generation, or complex instruction following. You cannot run Claude Opus 4, GPT-4o, or Gemini Ultra through MaxClaw.

OpenClaw lets you choose the best model for each agent independently. One agent can run Claude Opus 4 for complex reasoning while another runs a fast local Llama model for simple classification tasks. You can switch models without changing agent behavior — just update the model line in SOUL.md.

Cost Structure

MaxClaw charges a platform fee on top of compute costs. You pay for agent-hours and task executions at rates set by MiniMax. As your agent usage scales, costs scale accordingly and are harder to predict month to month.

OpenClaw has no platform fee — it is open-source. You pay only for the LLM API calls your agents make at the provider's published rates. If you use Ollama, there is no API cost at all, just the electricity and hardware running your machine. For high-volume agent workflows, this difference in cost structure can be substantial.

Vendor Lock-in

MaxClaw agent configurations are stored in MiniMax's proprietary format. If MiniMax changes pricing, deprecates features, or discontinues the service, migrating your agents requires manual reconstruction. Your workflows, tool integrations, and custom configurations are all tied to MaxClaw's platform.

OpenClaw's SOUL.md files are plain markdown text files that you own and control. They live in your file system, can be version-controlled with git, copied to any machine, and migrated to a different OpenClaw installation in seconds. There is no lock-in because there is no proprietary format.

Feature Comparison Table

Here is a direct side-by-side breakdown of how OpenClaw and MaxClaw compare across the dimensions that matter most for production agent deployments:

When to Use OpenClaw

OpenClaw is the right choice when control, privacy, and cost efficiency are priorities:

When to Use MaxClaw

MaxClaw is the right choice when speed of deployment and zero infrastructure overhead matter more than control:

Can You Use Both? The Hybrid Approach

Yes, and for many teams a hybrid deployment is the most pragmatic path. The key is to segment your workloads by data sensitivity and performance requirements, then match each segment to the right platform.

Use MaxClaw for agents that work with public or non-sensitive data and benefit from zero infrastructure management. Customer-facing chatbots answering FAQ-style questions, content summarization agents processing public web content, or marketing copy generation for public campaigns are all reasonable MaxClaw candidates.

Use OpenClaw (self-hosted) for agents that touch private business data, need access to your local file system, require integration with internal APIs, or process any information that should not leave your network. Your research analyst that reads internal documents, your data processing agent that queries your private database, and your customer data analysis agent should all run on self-hosted OpenClaw.

CrewClaw lets you configure multi-agent teams that span both environments. You can have a MaxClaw agent handling public web research pass outputs to a self-hosted OpenClaw agent that processes those findings against your private data — without the private data ever touching MaxClaw's infrastructure.

# Public-facing research (MaxClaw — non-sensitive, zero infra)
Agent: WebResearcher (MaxClaw)
- Role: Search the web for industry news and public data
- Model: MiniMax-Text-01
- Data: Public URLs and summaries only

# Internal analysis (OpenClaw, self-hosted — private data)
Agent: Analyst (OpenClaw, localhost)
- Role: Cross-reference web research with internal sales data
- Model: claude-opus-4-6 (or Ollama for fully offline)
- Data: Internal CRM records, never leaves your server

# Orchestration (CrewClaw)
- WebResearcher output → passes to Analyst
- Analyst accesses internal DB on your server
- Final report delivered via Slack (OpenClaw built-in channel)

Migration Considerations

Migrating from MaxClaw to OpenClaw

If you started with MaxClaw and want to move to self-hosted OpenClaw, the migration is feasible. MaxClaw agent configurations define role, instructions, and tool access. These map directly to OpenClaw's SOUL.md Identity, Rules, and Skills sections.

# MaxClaw agent definition (web dashboard)
Name: Content Researcher
Instructions: You are a research analyst. Find accurate
  information on given topics. Always cite sources.
  Prioritize recent data from credible publications.
Tools: web_search, document_parser
Model: MiniMax-Text-01

↓ Equivalent OpenClaw SOUL.md ↓

# Content Researcher

## Identity
- Name: ContentResearcher
- Role: Research Analyst
- Model: claude-opus-4-6   # or gpt-4o, gemini, ollama/llama3

## Personality
- Accurate and thorough
- Prioritizes recent data from credible publications

## Rules
- Always cite sources with URLs
- Prefer publications from the last 12 months
- Flag information older than 2 years

## Skills
- browser: Search the web for research data
- files: Parse and read documents

The main migration consideration is model selection. MaxClaw runs on MiniMax models that you cannot replicate exactly elsewhere. You will need to test your agent behavior with the model you choose in OpenClaw (Claude, GPT-4, Gemini, or a local model) and adjust the SOUL.md instructions to account for any differences in how the model responds.

Migrating from OpenClaw to MaxClaw

Going the other direction is simpler for basic agents. Your SOUL.md Identity becomes the agent name, your Personality and Rules become the instructions field, and your Skills map to MaxClaw's available built-in tools (or webhooks for custom integrations). The loss is model flexibility — you give up Claude, GPT-4, and Ollama and are constrained to MiniMax's model lineup.

More importantly, if your OpenClaw agents use Telegram or Slack integrations, you need to rebuild those connectors using MaxClaw's webhook system. This is non-trivial and requires hosting an additional service, which partially defeats the purpose of switching to a fully managed platform.

Cost Comparison: Self-Hosted vs Cloud

Cost is one of the most practical considerations and one where the two approaches diverge most sharply at scale.

For individual developers and small teams running fewer than 50 agent tasks per day, MaxClaw's convenience may justify the cost premium. For teams running agents continuously or at high volume, self-hosted OpenClaw with direct LLM API access becomes significantly cheaper as usage scales.

Related Guides

Frequently Asked Questions