GPT-4o vs Claude 3.5 vs Ollama — Which Model Works Best With OpenClaw?

OpenClaw supports all three. Each has genuine strengths and real limitations. Here is the honest comparison based on actual use across different task types.

The model question is the one most new OpenClaw users wrestle with first. The short answer: GPT-4o for general use and tool reliability, Claude 3.5 for complex reasoning and long documents, Ollama for privacy and cost. The longer answer depends on what you are actually doing.

GPT-4o — The Most Reliable for Tool Use

GPT-4o is OpenAI's flagship model and the one that OpenClaw was most extensively tested with. It has the best function calling reliability of the three — meaning it calls the correct skills with the correct parameters most consistently. For workflows involving many tool calls in sequence, GPT-4o produces the fewest errors.

It is also the fastest cloud option for most task types, handles parallel tool calling well (calling multiple skills simultaneously for latency reduction) and maintains coherent reasoning across long multi-step tasks.

The trade-off: cost. GPT-4o is more expensive per token than GPT-4o mini or Claude Haiku for simpler tasks. For complex reasoning tasks, the cost is justified. For simple daily automations, routing to GPT-4o mini saves significantly.

Claude 3.5 Sonnet — Best for Complex Reasoning and Documents

Anthropic's Claude 3.5 Sonnet is the best model for tasks that require careful, nuanced reasoning: analysing a complex contract, synthesising conflicting research, following intricate multi-condition instructions, or producing content that requires a specific voice and style.

Claude also handles very long documents better than GPT-4o — its 200,000-token context window is significantly larger, and it maintains coherence across the full context more consistently. For document analysis workflows, this matters substantially.

Ollama Local Models — Best for Privacy and Zero Cost

If privacy or cost are the primary considerations, Ollama wins unconditionally. Llama 3.1 8B runs on any machine with 8GB+ RAM, costs nothing per token, and keeps every message on your machine. For personal productivity tasks — file management, reminders, research, summarisation — it performs well, though measurably slower and less capable on complex reasoning than the cloud options.

The practical recommendation: use GPT-4o or Claude as your primary model and configure Ollama as a fallback for tasks that would be private or when you are offline. OpenClaw supports multiple models simultaneously and can route task types to the most appropriate model.