12 AI Models You Can Run with OpenClaw

Most AI tools lock you into a single provider. OpenClaw takes the opposite approach: it supports 12+ AI model providers through a unified interface, letting you switch between them with a single configuration change. Your skills, your workflows, your integrations -- they all carry over regardless of which model powers the backend.

This is not a minor feature. It is a fundamental architectural decision that shapes how skills get built, distributed, and maintained across the OpenClaw ecosystem.

Key Takeaways

• OpenClaw supports 12+ AI providers including Anthropic, OpenAI, Google, XAI, Moonshot, and more through a unified configuration system
• Model switching requires zero code changes -- skills written for one provider work identically across all supported models
• Each provider has distinct strengths for different use cases like coding, reasoning, creative work, and multilingual tasks
• OpenRouter and Vercel AI Gateway act as meta-providers, giving you access to dozens of additional models through a single API key
• Provider-agnostic skills are more valuable because they serve a wider audience in skill marketplaces and registries

The Complete Provider Lineup

OpenClaw's configuration wizard handles API key setup and model selection for each provider. Here is the full roster as of early 2026.

Provider Comparison Table

How Model Switching Works

OpenClaw's configuration system stores provider settings in your workspace. Switching models is a two-step process:

1. Run the configuration wizard to add your API key for the new provider
2. Set the active provider in your agent configuration

That is it. No code changes. No skill modifications. No integration rewiring.

This works because OpenClaw abstracts the provider layer. Skills interact with a unified API, and OpenClaw handles the translation to each provider's specific format. Function calling syntax differences, message format variations, token counting quirks -- all handled at the platform level.

Deep Dive: Each Provider's Sweet Spot

Anthropic (Claude)

Claude remains the strongest choice for coding tasks, complex reasoning, and long-context work. The Opus 4 family handles 200K+ token contexts reliably, making it ideal for skills that process entire codebases or lengthy documents.

Best use cases: Code generation, technical writing, analysis, agent orchestration

Limitations: Higher cost per token, no real-time information access

OpenAI (GPT)

GPT-4.5 brings strong general-purpose capabilities with excellent vision support and mature function calling. The broadest third-party ecosystem means more community resources and examples.

Best use cases: Vision tasks, general assistants, creative writing, broad API ecosystem

Limitations: Context window smaller than some competitors, rate limits on newer models

Google (Gemini)

Gemini 2.5 Pro offers massive context windows and strong multimodal capabilities. Native integration with Google services makes it powerful for workflows involving Search, Drive, or Gmail.

Best use cases: Multimodal processing, large document analysis, Google ecosystem integration

Limitations: Occasional inconsistency in complex reasoning chains

XAI (Grok)

Grok stands out for real-time information access and fewer content restrictions. It is particularly useful for skills that need current data or operate in domains where other models refuse to engage.

Best use cases: Real-time analysis, current events, unfiltered responses

Limitations: Smaller ecosystem, less mature function calling

Moonshot (Kimi K2.5)

Kimi excels at processing extremely long documents -- some versions handle 2M+ token contexts. It is also the strongest option for Chinese language tasks and cross-language workflows.

Best use cases: Long document processing, Chinese language, translation workflows

Limitations: English-language reasoning sometimes trails top-tier Western models

Meta-Providers: OpenRouter and Vercel AI Gateway

These are not individual models but gateways to dozens of them. OpenRouter provides a single API that routes to 100+ models, while Vercel AI Gateway adds edge deployment and streaming optimizations.

Why use them: Test multiple models without managing multiple API keys. Route different skills to different models based on cost or capability. Fall back automatically when a provider has downtime.

Provider-Agnostic Skills: Why It Matters

When you build a skill that works across all 12+ providers, you build something fundamentally more valuable than a provider-locked alternative.

Consider the math. A skill that only works with Claude serves perhaps 30% of the potential market. A skill that works across all providers serves 100%. In registries like ClawHub -- which now hosts over 13,000 skills -- provider-agnostic skills consistently see higher install counts.

This connects directly to how skill ecosystems develop. As we analyzed in our coverage of AI product development patterns, the most successful tools are those that reduce friction for the widest audience. Provider lock-in is friction.

Practical Configuration Patterns

Pattern 1: Cost Optimization

Use a cheaper model for routine tasks and a premium model for complex ones. OpenClaw lets you configure different providers for different agent roles:

• Triage agent: Qwen or MiniMax (low cost, fast responses)
• Analysis agent: Claude or GPT (high accuracy, strong reasoning)
• Translation agent: Kimi (specialized capability)

Pattern 2: Redundancy

Configure a primary and fallback provider. If Anthropic's API goes down, your agent automatically switches to OpenAI or Google. Uptime matters when skills run production workflows.

Pattern 3: Regional Compliance

Some organizations need data to stay within specific regions. Using providers with regional endpoints -- or self-hosted models through OpenRouter -- satisfies compliance requirements without changing skill code.

How This Compares to Other Platforms

Most AI agent platforms support one or two providers. Claude Code, for example, runs exclusively on Anthropic's models. That focus brings depth but limits flexibility. We explored this tradeoff in our comparison of the OpenClaw ecosystem.

OpenClaw's multi-provider approach means that the 13,000+ skills in ClawHub work regardless of which model a user prefers. A skill built for a GPT user works for a Claude user. A skill optimized for Grok works for a Gemini user. This interoperability is what makes the registry valuable at scale.

For a broader perspective on how skills flow between platforms and registries, see our analysis of the skill distribution landscape.

Setting Up Your First Provider

Getting started takes about two minutes:

1. Choose a provider from the table above
2. Get an API key from the provider's developer portal
3. Run OpenClaw's configuration wizard which walks you through key entry and model selection
4. Test with a simple prompt to verify the connection

The OpenClaw documentation covers provider-specific setup details, including rate limits, pricing tiers, and recommended models for different workloads.

FAQ

Can I use multiple providers simultaneously in a single OpenClaw instance?

Yes. OpenClaw supports configuring multiple providers and routing different agents or tasks to different models. You can run a Claude-powered coding agent alongside a Grok-powered research agent in the same workspace.

Do all skills work with all providers?

The vast majority do. Skills that use standard text generation and tool calling work across all providers. Skills that rely on provider-specific features -- like Anthropic's computer use or Google's native Search integration -- may be limited to those providers.

How does OpenClaw handle differences in function calling formats?

OpenClaw normalizes function calling at the platform level. You define tools once, and OpenClaw translates them to each provider's expected format (OpenAI-style function calling, Anthropic tool use, etc.).

Is there a performance difference between providers for the same skill?

Yes, and it can be significant. Complex reasoning tasks tend to perform best on Claude or GPT. Speed-sensitive tasks may benefit from lighter models through OpenRouter. The best approach is to test your specific skills across providers and benchmark the results.

Does switching providers affect my conversation history or memory?

No. OpenClaw's memory system (MEMORY.md) is provider-independent. Your agent retains context and learned preferences regardless of which model processes the next message.

The Provider-Agnostic Future

The AI model landscape changes fast. Six months ago, several of these providers did not exist or were not competitive. Six months from now, the leaderboard will look different again.

Building on a platform that supports 12+ providers is not about picking the best model today. It is about ensuring your skills, workflows, and automations survive the next model generation -- and the one after that.

Explore production-ready AI skills at aiskill.market/browse or submit your own skill to the marketplace.