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LLM ComparisonClaude 4.1 OpusClaude 3 Haiku

Claude 4.1 Opus vs Claude 3 Haiku

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

Model Comparison

FeatureClaude 4.1 OpusClaude 3 Haiku
ProviderAnthropicAnthropic
Model Typetexttext
Context Window1,000,000 tokens200,000 tokens
Input Cost
$15.00/ 1M tokens
$0.25/ 1M tokens
Output Cost
$75.00/ 1M tokens
$1.25/ 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 Haiku

Anthropic

1. Speed

  • Fastest model in the Claude 3 family
  • Near-instant responses for chat, support, and live tools

2. Efficiency

  • Most affordable model
  • Ideal for massive-scale applications and low-latency use cases

3. Practical Use Cases

  • Customer support
  • Translations
  • Moderation
  • Logistics, inventory systems
  • Extracting insights from unstructured data

4. Vision Skills

  • Handles charts, images, and diagrams quickly
  • Useful for scanning large volumes of visual data

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