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LLM ComparisonClaude 4.5 SonnetClaude 4.1 Opus

Claude 4.5 Sonnet vs Claude 4.1 Opus

Compare Claude 4.5 Sonnet and Claude 4.1 Opus. Build AI products powered by either model on Appaca.

Model Comparison

FeatureClaude 4.5 SonnetClaude 4.1 Opus
ProviderAnthropicAnthropic
Model Typetexttext
Context Window1,000,000 tokens1,000,000 tokens
Input Cost
$3.00/ 1M tokens
$15.00/ 1M tokens
Output Cost
$15.00/ 1M tokens
$75.00/ 1M tokens

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Strengths & Best Use Cases

Claude 4.5 Sonnet

Anthropic

1. Best-in-class coding performance

  • #1 on SWE-bench Verified (77.2% standard, 82.0% high-compute).
  • Excels at debugging, architecture, and multi-file code generation.
  • Maintains coherence for extremely long tasks (30+ hours).

2. State-of-the-art computer use & agents

  • Leads OSWorld at 61.4%.
  • Strongest model for agentic workflows, multi-step tool use, and real computer control.
  • Powering Claude Code, the new Claude Agent SDK, and Chrome agent actions.

3. Advanced reasoning & math

  • Large improvements across reasoning-heavy benchmarks (AIME, MMMLU, τ2-bench, Terminal-Bench).
  • Deep multi-step reasoning with extended or interleaved thinking.

4. High alignment & safety

  • Most aligned Claude model to date with reduced deception, hallucinations, sycophancy, and harmful compliance.
  • Strong protections against prompt injection for agentic tasks (ASL-3 safeguards).

5. Domain-expert performance

  • Notable gains in finance, law, medicine, and STEM tasks.
  • Trusted by early customers for long-context legal analysis, multi-file engineering, security research, and red-teaming.

Claude 4.1 Opus

Anthropic

1. Advanced Coding Performance

  • Achieves 74.5% on SWE-bench Verified, improving the Claude family's state-of-the-art coding abilities.

  • Stronger at:

    • Multi-file code refactoring
    • Large codebase debugging
    • Pinpointing exact corrections without unnecessary edits
  • Outperforms Opus 4 and shows gains comparable to jumps seen in past major releases.

2. Improved Agentic & Research Capabilities

  • Better at maintaining detail accuracy in long research tasks.
  • Enhanced agentic search and step-by-step problem solving.
  • Performs reliably across complex multi-turn reasoning tasks.

3. Validated by Real-World Users

  • GitHub: Better multi-file refactoring and code adjustments.
  • Rakuten Group: High precision debugging with minimal collateral changes.
  • Windsurf: One standard deviation improvement on their junior dev benchmark - similar magnitude to Sonnet 3.7 → Sonnet 4.

4. Hybrid-Reasoning Benchmark Improvements

  • Improvements across TAU-bench, GPQA Diamond, MMMLU, MMMU, AIME (with extended thinking).
  • Stronger robustness in long-context reasoning tasks.

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