Compare GPT-4.1 and GPT-4.1 Nano. Find out which model is better for your specific use case and requirements.
| Feature | GPT-4.1 | GPT-4.1 Nano |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Model Type | text | text |
| Context Window | 1,047,576 tokens | 1,047,576 tokens |
| Input Cost | $2.00/ 1M tokens | $0.10/ 1M tokens |
| Output Cost | $8.00/ 1M tokens | $0.40/ 1M tokens |
1. Smartest non-reasoning model
2. Excellent instruction following
3. Reliable tool calling
4. Large 1M-token context window
5. Low latency (no reasoning step)
6. Multimodal input
7. Supports fine-tuning
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
Discover AI prompts that work great with these models. Use them to build powerful AI tools on Appaca.
Create a training program for the sales team to communicate your USP and address persona challenges with consistent messaging and proof.
Estimate preliminary cost ranges for common land improvements (clearing, driveway, perc, utilities) and identify the best ROI for a flip.
Generate high-converting email subject lines that boost open rates using proven psychological triggers and A/B testing frameworks.
Design a lead scoring model that prioritizes prospects based on engagement with USP messaging and signals of persona challenge severity.
Create clear, measurable learning objectives aligned to standards using Blooms Taxonomy action verbs.
Create a training program for the sales team to communicate your USP and address persona challenges with consistent messaging and proof.
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