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Compare o1 and Claude 3.5 Sonnet. Build AI products powered by either model on Appaca.
Model Comparison
| Feature | o1 | Claude 3.5 Sonnet |
|---|---|---|
| Provider | OpenAI | Anthropic |
| Model Type | text | text |
| Context Window | 200,000 tokens | 200,000 tokens |
| Input Cost | $15.00/ 1M tokens | $3.00/ 1M tokens |
| Output Cost | $60.00/ 1M tokens | $15.00/ 1M tokens |
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Build your first app freeStrengths & Best Use Cases
o1
OpenAI1. Full-scale reasoning model
- Uses reinforcement learning to generate long internal chains of thought.
- Suitable for tasks requiring deep logic, multi-step planning, and rich analytical reasoning.
2. Strong performance across domains
- Excellent at math, science, coding, and structured analytical work.
- Handles multi-step workflows and complex problem-solving with high consistency.
3. High output capacity (100K tokens)
- Enables long, detailed explanations, large documents, and multi-part analyses.
4. Image-understanding capable
- Accepts text + image inputs for visual reasoning and mixed-modality tasks.
- Output is text only, optimized for clear explanations.
5. Advanced API compatibility
- Works with Chat Completions, Responses, Realtime, Assistants, and more.
- Supports streaming, function calling, and structured outputs.
6. Stable long-context performance
- 200K-token context window supports large files, multi-document analysis, and extended conversations.
7. Designed for correctness-oriented workloads
- Prioritizes rigorous reasoning over speed.
- Useful in auditing, verification, scientific thinking, policy analysis, and legal-style reasoning.
8. Powerful but expensive
- High token costs make it suitable for selective, mission-critical reasoning rather than high-volume usage.
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 o1
textLocal SEO Landing Page Copy
Write location-specific landing page copy to rank in local search results.
Short Sale Listing Description
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Best for Claude 3.5 Sonnet
textGitHub README File
Write a comprehensive README file for an open source or internal project.
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