Compare GPT-4.1 Nano and Claude 3.5 Haiku. Find out which model is better for your specific use case and requirements.
| Feature | GPT-4.1 Nano | Claude 3.5 Haiku |
|---|---|---|
| Provider | OpenAI | Anthropic |
| Model Type | text | text |
| Context Window | 1,047,576 tokens | 200,000 tokens |
| Input Cost | $0.10/ 1M tokens | $0.80/ 1M tokens |
| Output Cost | $0.40/ 1M tokens | $4.00/ 1M tokens |
1. Ultra-Fast, Low-Latency Performance
2. Most Cost-Efficient GPT-4.1 Variant
3. Solid Instruction Following
4. Strong Tool Calling Capabilities
5. Basic Multimodal Input
6. Text-Only Output
7. 1M-Token Context Window
8. Ideal Use Cases
9. Broad API Integration
1. Intelligence & Benchmark Performance
2. Coding Strength
Scores 40.6% on SWE-bench Verified, outperforming:
Excellent for engineering assistants, agent coding tasks, and bug fixing.
3. Speed & Latency
4. Tool Use & Instruction Following
5. Best Use Cases
Discover AI prompts that work great with these models. Use them to build powerful AI tools on Appaca.
Analyze financial statements to understand company health, trends, and investment potential.
Create video tutorials that teach your persona how to implement your USP solution against specific challenges with clear, actionable guidance.
Create an ABM campaign targeting high-value accounts with tailored messages that connect persona challenges to your USP.
Review a legal document for citation format issues and propose precise corrections without changing substantive meaning.
Brainstorm unique, buyer-friendly land use ideas based on zoning, topography, and nearby attractions to boost perceived value.
Identify top counties/metros for vacant land flips by comparing appreciation, liquidity, and demand signals across target regions.
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