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Get started freeClaude 4.1 Opus vs Claude 3.5 Sonnet
Compare Claude 4.1 Opus and Claude 3.5 Sonnet. Build AI products powered by either model on Appaca.
Model Comparison
| Feature | Claude 4.1 Opus | Claude 3.5 Sonnet |
|---|---|---|
| Provider | Anthropic | Anthropic |
| Model Type | text | text |
| Context Window | 1,000,000 tokens | 200,000 tokens |
| Input Cost | $15.00/ 1M tokens | $3.00/ 1M tokens |
| Output Cost | $75.00/ 1M tokens | $15.00/ 1M tokens |
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Build your first app freeStrengths & Best Use Cases
Claude 4.1 Opus
Anthropic1. Advanced Coding Performance
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Achieves 74.5% on SWE-bench Verified, improving the Claude family's state-of-the-art coding abilities.
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Stronger at:
- Multi-file code refactoring
- Large codebase debugging
- Pinpointing exact corrections without unnecessary edits
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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 3.5 Sonnet
Anthropic1. Intelligence & Reasoning
- Outperforms previous Claude models and competitor LLMs across major benchmarks.
- Excels in graduate-level reasoning (GPQA), knowledge tasks (MMLU), and coding (HumanEval).
- Handles nuance, humor, and complex instructions with human-like clarity.
2. Speed & Efficiency
- Runs 2x faster than Claude 3 Opus, making it ideal for real-time and high-volume workflows.
- Cost-effective pricing: $3/M input tokens and $15/M output tokens.
- Supports a 200K token context window, enabling rich, long-form reasoning.
3. Coding Capabilities
- Solves significantly more coding and bug-fix tasks (64% vs Opus's 38% in internal evaluations).
- Can autonomously write, edit, and execute code when tool use is enabled.
- Strong at translating and modernizing legacy codebases.
4. Vision Strength
- Best vision model in the Claude family, surpassing Opus on vision benchmarks.
- Excellent at interpreting charts, graphs, and imperfect images.
- Reliable text extraction from low-quality visuals for retail, logistics, finance, etc.
5. Agentic Workflows
- Highly capable for multi-step task orchestration.
- Performs well as the engine for agents requiring reasoning, planning, and tool-calling abilities.
6. Content Quality
- Produces natural, relatable writing with improved tone, style, and context awareness.
- Strong at long-form content creation and editing.
7. Safety & Reliability
- Rated ASL-2, meeting Anthropic's safety standards.
- Undergoes extensive red-teaming and external evaluation (UK AISI & US AISI).
- Not trained on user data without explicit permission.
Prompts to Get Started
Use these prompts to power AI products you build on Appaca. Each works great with the models above.
Best for Claude 4.1 Opus
textBug Report Template
Write a thorough bug report that gives developers everything needed to reproduce.
Listicle Writing
Write an engaging listicle article with actionable numbered points.
Inquiry-Based Learning Unit
Design an inquiry-based learning unit centred on a driving question.
Best for Claude 3.5 Sonnet
textContract Review Checklist
Create a checklist for reviewing any commercial contract before signing.
Inbox Zero Strategy
Create a personalised system to achieve and maintain inbox zero.
Marketing Tech Stack (MarTech) Recommendations
Design a marketing technology stack that supports executing and measuring persona-targeted campaigns centered on your USP and challenges.