Claude vs GPT for AI Agents: Cost and Performance Compared

The model landscape

As of early 2025, the main options for agent workloads are:

• Claude Opus 4 — Anthropic's top model. Best reasoning. Most expensive.
• Claude Sonnet 4 — Anthropic's mid-tier. Excellent for most agent tasks. 5x cheaper than Opus.
• Claude Haiku 4 — Anthropic's fast/cheap tier. Good for monitoring, routing, classification.
• GPT-4o — OpenAI's flagship. Strong reasoning, multimodal, widely used.
• GPT-4o mini — OpenAI's fast/cheap tier. Excellent price-to-performance for simple tasks.

OpenClaw supports all of these. You configure the model per task type in openclaw.json.

Pricing comparison

Relative cost is normalized to Sonnet 4 as 2x, with Sonnet being the common middle-ground model. GPT-4o mini is dramatically cheaper than everything else if you only need simple classification or routing.

Context window: why it matters for agents

Agent workloads tend to have long contexts. You have workspace files (9,000+ tokens), then the actual task, then potentially tool results, then the model's reasoning, then the response. A complex coding task with file contents can easily hit 40,000 to 60,000 tokens.

Claude models (Opus, Sonnet, Haiku) all have 200k context windows. GPT-4o has 128k. GPT-4o mini has 128k.

For most agent tasks, 128k is enough. Where it matters: very long document analysis, large codebase review, or extended multi-turn conversations with lots of history. If you frequently bump into context limits, the 200k window matters.

In practice, the difference is rarely the deciding factor. Most tasks fit in 128k.

Quality comparison for agent-specific workloads

Instruction following and tool use.

Both families are good at following structured instructions and using tools. Claude models have historically been more reliable with strict JSON output and complex tool schemas. GPT-4o is competitive here and has a larger ecosystem of integrations. For OpenClaw specifically, Claude is the better-tested path since OpenClaw is designed around Anthropic models.

Reasoning and code.

Claude Opus 4 and GPT-4o are close peers on hard reasoning and coding tasks. Both are significantly better than their respective cheaper tiers for complex problems. For most code review, debugging, and architectural reasoning, either works well. Claude Opus tends to be more verbose and thorough. GPT-4o tends to be more direct.

Simple monitoring and classification.

GPT-4o mini and Claude Haiku are both excellent here. This is where GPT-4o mini shines: at $0.15/MTok input, it is 5x cheaper than Haiku and nearly as capable for classification, routing, and simple checks. If cost is your primary concern for heartbeat-style tasks, GPT-4o mini is worth testing.

Content generation.

Claude models write with better tone control and follow style guidelines more consistently. GPT-4o writes well but is more prone to generic phrasing. For blog posts, summaries, or communication drafts, Claude Sonnet is generally the better choice. GPT-4o mini is not recommended for content that needs quality voice.

Which model family for OpenClaw?

OpenClaw was built primarily around Claude. The system prompts, skill descriptions, and behavior guidelines are tuned for Claude's response patterns. Claude models will generally work better out of the box.

That said, OpenClaw supports GPT models and they work. The practical tradeoffs:

The cost of mixing families

Using GPT-4o mini for heartbeats while running Claude Sonnet for the main agent is a valid strategy if you have already tested that GPT-4o mini handles your specific heartbeat tasks reliably. The cost savings are real: GPT-4o mini at $0.15/MTok vs Haiku at $0.80/MTok is another 5x reduction.

The risk: mixing model families adds complexity. Testing that your heartbeat prompt works correctly with GPT-4o mini takes time. For most users, sticking with one family and routing within it (Opus/Sonnet/Haiku) is simpler and still very cost-effective.

A practical default recommendation

If you are starting from scratch:

1. Main model: Claude Sonnet 4 — best balance of quality and cost for primary agent work
2. Heartbeat model: Claude Haiku 4 — simple tasks, proven to work with OpenClaw
3. Sub-agent model: Claude Sonnet 4 — same as main, consistent behavior
4. Complex reasoning tasks: Claude Opus 4 — only when you need deep analysis

This config runs around $25 to $60/month for typical usage (1 channel, 30-minute heartbeats, 30 messages/day). It gives you Opus quality when it matters and Haiku prices for background noise.