Claude Sonnet 4.6 vs Opus 4.6: Complete Benchmark Comparison
Detailed comparison of Claude Sonnet 4.6 and Opus 4.6: benchmarks, pricing, use cases, and when to choose each model for your AI applications.
TL;DR
Claude Sonnet 4.6 matches 98-99% of Opus 4.6 performance on coding and computer use at 1/5th the cost. Opus 4.6 only pulls ahead significantly on expert reasoning (GPQA: 91.3% vs 74.1%) and needle-in-haystack retrieval. Default to Sonnet 4.6; escalate to Opus only when you need maximum reasoning depth.
The Value Proposition
With Sonnet 4.6, Anthropic has essentially democratized flagship-level AI. What would have required a $15/$75 Opus model just months ago is now achievable at $3/$15—a 5x cost reduction with negligible quality loss for most applications.
Benchmark Comparison
| Benchmark | Sonnet 4.6 | Opus 4.6 | Gap |
|---|
| SWE-bench Verified | 79.6% | 80.8% | 1.2% |
| OSWorld-Verified | 72.5% | 72.7% | 0.2% |
| GPQA Diamond | 74.1% | 91.3% | 17.2% |
| Math (AIME) | 89% | 93% | 4% |
| GDPval-AA (Office) | 1633 | 1606 | Sonnet wins |
| Finance Agent v1.1 | 63.3% | 60.1% | Sonnet wins |
| MRCR v2 (1M needle) | ~18% | 76% | 58% |
Where They're Essentially Tied
Coding (SWE-bench): 79.6% vs 80.8%—a 1.2% gap that's within noise for most real-world applications. Both models handle complex multi-file refactoring, debugging, and feature implementation with equal reliability.
Computer Use (OSWorld): 72.5% vs 72.7%—functionally identical. Both excel at web browsing, form automation, and desktop tasks.
Where Sonnet 4.6 Actually Wins
Office Tasks (GDPval-AA): Sonnet scores 1633 Elo vs Opus's 1606. For spreadsheet work, document processing, and knowledge tasks, Sonnet is measurably better.
Financial Analysis: Sonnet leads 63.3% vs 60.1% on agentic financial benchmarks—surprising given Opus's reputation for deep reasoning.
Where Opus 4.6 Justifies Its Premium
Expert Reasoning (GPQA): Opus's 91.3% vs Sonnet's 74.1% represents a significant gap. For PhD-level science questions, medical diagnosis, or legal analysis, Opus delivers substantially better results.
Long-Context Retrieval: On the 8-needle 1M variant of MRCR v2, Opus scores 76% vs Sonnet's ~18%. If your application requires finding specific information buried in massive documents, Opus is necessary.
Multi-Agent Coordination: Opus 4.6 with Agent Teams handles complex orchestration tasks where multiple AI agents must collaborate.
Pricing Analysis
| Model | Input | Output | Monthly Cost (1M tokens/day) |
|---|
| Sonnet 4.6 | $3 | $15 | ~$540 |
| Opus 4.6 | $15 | $75 | ~$2,700 |
At scale, the difference is dramatic: $2,160/month savings by defaulting to Sonnet.
Decision Framework
Default to Sonnet 4.6 when:
- Building coding assistants or dev tools
- Creating automation/computer-use agents
- Processing documents and spreadsheets
- Running customer support or chatbots
- Cost efficiency matters
- Response speed is important
- Tasks require PhD-level scientific reasoning
- Searching for needles in million-token haystacks
- Coordinating multiple AI agents
- Maximum accuracy justifies 5x cost
- Working on novel research problems
Escalate to Opus 4.6 when:
Hybrid Strategy
Many teams implement a routing strategy:
if task.requires_expert_reasoning or task.context > 500k:use_opus()
else:
use_sonnet() # 90%+ of requests
This captures Opus capabilities when needed while maintaining cost efficiency.
Conclusion
Sonnet 4.6 has made Opus 4.6 a specialist tool rather than a general-purpose default. For most applications, Sonnet delivers indistinguishable results at 20% of the cost. Reserve Opus for expert reasoning, massive context retrieval, and multi-agent coordination.