import ComparisonTable from ’../../components/ComparisonTable.astro’;
OpenAI o3 and Claude Opus 4 represent the current frontier of AI reasoning. Both are expensive, deliberate thinking models designed for tasks that require sustained analytical effort — not casual queries.
Quick Verdict
Choose o3 if: You’re solving hard math, competitive programming, or scientific problems where benchmark performance directly matters.
Choose Claude Opus if: Nuanced writing quality, instruction following, and reliable behavior in complex prompts are your priorities.
Specifications
<ComparisonTable headers={[“Spec”, “OpenAI o3”, “Claude Opus 4”]} rows={[ [“Reasoning approach”, “Chain-of-thought (internal)”, “Extended thinking (visible)”], [“Context window”, “200K tokens”, “200K tokens”], [“API input cost”, “$10/M tokens”, “$15/M tokens”], [“API output cost”, “$40/M tokens”, “$75/M tokens”], [“Reasoning tokens”, “Separate pricing”, “Included in output”], [“Multimodal”, “Image + text”, “Image + text”], [“Latency”, “Slower (2-5 min for hard)”, “Slower (extended thinking)”], [“Best use”, “Hard reasoning tasks”, “Reasoning + writing”], ]} />
Benchmark Performance
o3 holds leads on the hardest AI benchmarks:
- AIME 2024: o3 ~90% vs Opus ~70%
- SWE-bench: o3 ~71% vs Opus ~49%
- GPQA Diamond: o3 ~87% vs Opus ~75%
These are genuinely hard problems — undergraduate math competitions, competitive programming, PhD-level science questions. If your task resembles these, o3’s advantage is real.
For typical business tasks (writing, analysis, summarization), these benchmark differences disappear in practice.
Reasoning Transparency
Claude Opus’s extended thinking shows its reasoning chain in the response. This is valuable for:
- Verifying the reasoning approach, not just the answer
- Educational contexts where process matters
- Debugging why the model reached a conclusion
o3’s reasoning is internal and not visible to users (OpenAI’s architecture choice).
Winner: Claude Opus for transparency
Writing and Communication
For complex professional writing — analysis reports, strategy documents, nuanced explanations — Claude Opus consistently outperforms o3. o3 is optimized for correct answers, not elegant prose.
Winner: Claude Opus for writing quality
Cost at Scale
Both are expensive. For complex reasoning tasks that previously required hours of expert time, the ROI calculation is straightforward: if o3 or Opus saves 4 hours of $300/hour consulting time, the $10-50 API cost is trivially justified.
At scale (millions of tokens), o3 is somewhat cheaper than Opus.
Latency
Both models are slow for complex tasks — this is by design. Reasoning models “think before they answer.”
- Simple queries: 5-30 seconds
- Complex reasoning: 1-5 minutes
- Very hard problems: 5-20+ minutes
Neither model is appropriate for latency-sensitive applications.
When to Use Each
| Task | Best Model |
|---|---|
| Competition math | o3 |
| Scientific research | o3 |
| Competitive programming | o3 |
| Complex code debugging | o3 (slight edge) |
| Business analysis | Claude Opus |
| Long-form writing | Claude Opus |
| Multi-constraint reasoning | Claude Opus |
| Legal/medical analysis | Claude Opus (reliability) |
Bottom Line
o3 is the frontier leader on measurably hard reasoning tasks. Claude Opus is the better general-purpose reasoning model for professional work that requires nuanced judgment alongside analytical depth. If you’re solving competition math problems, use o3. If you’re writing strategy memos, use Opus.