What AI models does the agent use?

The agent has access to Claude, DeepSeek, Gemini, and other top models. It automatically routes to the best model for each task — you never have to think about API keys or token limits.

Yes. Each agent runs in an isolated environment. We don't train on your data, and you can export or delete everything at any time. The underlying engine (GoGogot) is open-source, so you can audit exactly how it works.

What can the agent actually do?

Browse the web, process files (CSV, PDF, images), run scheduled tasks, remember context across sessions, and communicate via Telegram or Slack. Think of it as a capable junior employee, not a chatbot.

How does memory work?

The agent maintains persistent memory across sessions. It remembers your preferences, past conversations, and task context. You can also explicitly tell it to remember or forget things.

Can I self-host the agent?

Absolutely. GoGogot is 100% open-source. Run it on your own hardware for free. cowork.ink is the managed version — we handle servers, model costs, updates, and uptime so you don't have to.

Is there a free trial?

We offer a 7-day money-back guarantee. Spin up an agent, give it real tasks, and if it doesn't save you time, we'll refund you — no questions asked.

Which model is the cheapest to run with OpenClaw?

DeepSeek V3.2 at $0.28/$1.10 per million tokens (input/output) is the cheapest capable model — sessions cost roughly $0.02. Gemini 2.5 Flash ($0.15/$0.60) is even cheaper for simpler tasks but less reliable at complex tool calling.

Can I use a free model with OpenClaw?

Yes. Gemini offers a free tier for most models, and Llama 4 weights are free to self-host. You can also use Groq's free tier for Llama at ~$0.11 per million input tokens. See our [OpenClaw tutorial](/blog/openclaw-tutorial/) for setup instructions.

Does OpenClaw work with local models?

Yes. OpenClaw supports any OpenAI-compatible API, so you can point it at Ollama, LM Studio, or vLLM running Llama 4, Qwen, or Mistral locally. Expect slower responses and weaker tool calling compared to cloud APIs.

Should I use the same model for every OpenClaw task?

No. The smartest setup is model routing — use a cheap model (DeepSeek, Gemini Flash) for simple queries and escalate to Claude or GPT for complex multi-step tasks. OpenClaw's multi-model support makes this easy.

Which model has the best tool calling for OpenClaw?

Claude Sonnet 4.6 leads the PinchBench OpenClaw benchmark at 86.9% success rate and scores highest on MCP-based benchmarks (71.6 on MCPAgentBench). GPT-5.4 is close at 86.0% on PinchBench. For OpenClaw specifically, Claude and GPT are the safest choices for complex workflows.

Best AI Model for OpenClaw: Claude vs. GPT vs. Gemini vs. DeepSeek (2026)

TESTED: Claude, GPT, Gemini, DeepSeek & Llama on real OpenClaw tasks. Pricing, benchmarks & which model wins for YOUR use case. Compare now.

Frequently Asked Questions

Which model is the cheapest to run with OpenClaw?: DeepSeek V3.2 at $0.28/$1.10 per million tokens (input/output) is the cheapest capable model — sessions cost roughly $0.02. Gemini 2.5 Flash ($0.15/$0.60) is even cheaper for simpler tasks but less reliable at complex tool calling.
Can I use a free model with OpenClaw?: Yes. Gemini offers a free tier for most models, and Llama 4 weights are free to self-host. You can also use Groq's free tier for Llama at ~$0.11 per million input tokens. See our [OpenClaw tutorial](/blog/openclaw-tutorial/) for setup instructions.
Does OpenClaw work with local models?: Yes. OpenClaw supports any OpenAI-compatible API, so you can point it at Ollama, LM Studio, or vLLM running Llama 4, Qwen, or Mistral locally. Expect slower responses and weaker tool calling compared to cloud APIs.
Should I use the same model for every OpenClaw task?: No. The smartest setup is model routing — use a cheap model (DeepSeek, Gemini Flash) for simple queries and escalate to Claude or GPT for complex multi-step tasks. OpenClaw's multi-model support makes this easy.
Which model has the best tool calling for OpenClaw?: Claude Sonnet 4.6 leads the PinchBench OpenClaw benchmark at 86.9% success rate and scores highest on MCP-based benchmarks (71.6 on MCPAgentBench). GPT-5.4 is close at 86.0% on PinchBench. For OpenClaw specifically, Claude and GPT are the safest choices for complex workflows.