Comparing AI Models in 2026: Which Model Works Best with OpenClaw?

Introduction

OpenClaw is model-agnostic: you can connect any large language model via an API key. But which model should you choose? In early 2026 there are more options than ever, each with its own strengths, pricing models, and privacy policies. Your choice directly impacts the quality of your AI assistant, the monthly cost, and what happens to your data.

We tested the four most popular models in a realistic OpenClaw scenario: daily use as a personal assistant with tasks ranging from email summarization to calendar management and code reviews. Here are our findings.

Claude 3.5 Sonnet: The All-Rounder

Claude 3.5 Sonnet from Anthropic is currently the default model for most OpenClaw users, and for good reason. The model consistently scores high on both language comprehension and executing complex multi-step tasks. When summarizing long email threads, Claude picks up on nuances that other models miss — it recognizes sarcasm and implicit requests, for example.

Costs are around three dollars per million input tokens and fifteen dollars per million output tokens. With average usage (fifty to one hundred interactions per day) that comes to eight to fifteen dollars per month. The 200K token context window means Claude can process complete documents and long conversation histories without losing information.

The main downside is speed. Claude is noticeably slower than GPT-4o for short, quick tasks. For answering a simple question you wait an average of two to three seconds, while GPT-4o responds within a second.

GPT-4o: Speed and Versatility

OpenAI's GPT-4o is the fastest premium model in this comparison. Response time consistently falls under one second for short requests, which makes it particularly pleasant for quick questions via WhatsApp or Telegram. The model handles multimodal input well — send a photo of a whiteboard and GPT-4o reliably transcribes the text.

Cost-wise GPT-4o is comparable to Claude: two dollars fifty per million input tokens and ten dollars per million output tokens. The context window is 128K tokens, more than enough for most tasks but noticeably smaller than Claude's when processing very long documents.

A consideration for European users: data processed through the OpenAI API passes through servers in the United States. OpenAI promises that API data is not used for training, but the jurisdiction may be relevant for those who want to stay strictly under GDPR.

Gemini 2.0 Flash and DeepSeek-V3: The Budget Options

For users who want to keep costs low, Google's Gemini 2.0 Flash and DeepSeek-V3 are interesting alternatives. Gemini Flash costs only a fraction of Claude and GPT-4o, and Google AI Studio's free tier is generous enough for light personal use. Quality is good for straightforward tasks like calendar management and simple summaries, but the model stumbles more often with complex multi-step reasoning.

DeepSeek-V3 is the Chinese open-weight model that caused a stir in late 2025 by delivering performance close to GPT-4 at a fraction of the cost. You can call it via the DeepSeek API for about one dollar fourteen per million input tokens. However, quality in languages other than English and Chinese is noticeably lower — the model was primarily trained on those two languages.

For those who want maximum privacy: DeepSeek-V3 can be run locally via Ollama if you have a machine with at least 32 GB RAM (or a GPU with 24 GB VRAM). This eliminates all API costs and keeps your data entirely local, but response times are significantly longer.

Our Recommendation per Use Case

There is no single "best" model — it depends on your priorities. For daily use as a personal assistant with a mix of tasks, we recommend Claude 3.5 Sonnet: the quality justifies the slightly higher cost and slower speed. For fast chat-based interactions where response time is critical, GPT-4o wins. For budget-conscious use or experimentation, Gemini Flash is a solid starting point.

OpenClaw also supports model routing: you can configure simple tasks (like reminders and weather updates) to go to a cheaper model, while complex tasks (like email summaries and document analysis) are sent to Claude. This hybrid approach can reduce your monthly costs by forty to sixty percent without noticeable quality loss.

Conclusion

The AI model landscape changes rapidly, and prices consistently drop. What costs fifteen dollars a month today might cost five dollars in six months. The beauty of OpenClaw is that you can switch at any time without data loss — your entire conversation history and configuration remain intact. Start with the model that best fits your budget and needs, and experiment from there.