The o1 series of models are trained with reinforcement learning to think before they answer and perform complex reasoning. The o1-pro model uses more compute to think harder and provide...
Model details →OpenAI: o1-pro (batch) vs Anthropic: Claude Opus Latest
Anthropic: Claude Opus Latest wins on 4 of 6 axes — pricing and capability skew in its favour for most workloads.
This model always redirects to the latest model in the Claude Opus family.
Model details →Side-by-side comparison
| Capability | OpenAI: o1-pro (batch) | Anthropic: Claude Opus Latest | Winner |
|---|---|---|---|
| Context window Maximum number of input tokens the model can attend to in a single request. | 200K | 1M | 🏆 Anthropic: Claude Opus Latest |
| Input price (per 1M) Cost per million input tokens billed by the provider. | $75.00 | $5.00 | 🏆 Anthropic: Claude Opus Latest |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $300.00 | $25.00 | 🏆 Anthropic: Claude Opus Latest |
| Tool / function calling First-class support for emitting structured tool calls. | — | Yes | 🏆 Anthropic: Claude Opus Latest |
| Vision input Accepts image inputs alongside text. | Yes | Yes | Tie |
| Reasoning mode Internal chain-of-thought / extended-thinking support. | Yes | Yes | Tie |
Frequently asked questions
Is OpenAI: o1-pro (batch) better than Anthropic: Claude Opus Latest?
Anthropic: Claude Opus Latest wins on 4 of 6 axes — pricing and capability skew in its favour for most workloads.
What's the price difference between OpenAI: o1-pro (batch) and Anthropic: Claude Opus Latest?
Input: $75.00 vs $5.00 per 1M tokens. Output: $300.00 vs $25.00 per 1M tokens.
What context windows do OpenAI: o1-pro (batch) and Anthropic: Claude Opus Latest support?
OpenAI: o1-pro (batch) supports up to 200K tokens. Anthropic: Claude Opus Latest supports up to 1M tokens.
Do both OpenAI: o1-pro (batch) and Anthropic: Claude Opus Latest support tool calling?
OpenAI: o1-pro (batch): not advertised. Anthropic: Claude Opus Latest: yes.
Compare OpenAI: o1-pro (batch) with other models
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