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LLM ComparisonClaude 4.1 OpusClaude 3 Opus

Claude 4.1 Opus vs Claude 3 Opus

Compare Claude 4.1 Opus and Claude 3 Opus. Build AI products powered by either model on Appaca.

Model Comparison

FeatureClaude 4.1 OpusClaude 3 Opus
ProviderAnthropicAnthropic
Model Typetexttext
Context Window1,000,000 tokens200,000 tokens
Input Cost
$15.00/ 1M tokens
$15.00/ 1M tokens
Output Cost
$75.00/ 1M tokens
$75.00/ 1M tokens

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Strengths & Best Use Cases

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.

Claude 3 Opus

Anthropic

1. Intelligence & Reasoning

  • Highest capability in the Claude 3 family
  • Near-human comprehension and fluency
  • Excels at MMLU, GPQA, GSM8K, advanced reasoning tasks

2. Complex Problem Solving

  • Best for research, strategy, multi-step planning
  • Handles ambiguous, open-ended tasks with ease

3. Vision & Multimodal Capabilities

  • Strong chart/graph understanding
  • Processes documents, technical diagrams, and dense visual data

4. Recall & Long-Context Reasoning

  • Near-perfect recall (>99% on NIAH benchmark)
  • Handles very large documents and multi-file workflows

5. Enterprise-Grade Accuracy

  • Significantly reduced hallucinations
  • High correctness rate for factual queries