Cost Comparison (1000 input + 500 output tokens, 100 requests/day)
GPT-5 nano
o1
Cost Differences
o1 costs more than GPT-5 nano
Feature Comparison
| Feature | GPT-5 nano | o1 |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Input Price | $0.05/1M tokens | $15.00/1M tokens |
| Output Price | $0.40/1M tokens | $60.00/1M tokens |
| Context Window | 128,000 tokens | 200,000 tokens |
| Max Output | 8,192 tokens | 65,536 tokens |
| Category | efficient | reasoning |
| Capabilities | text | textreasoning |
| Release Date | 8/7/2025 | 9/12/2024 |
GPT-5 nano vs o1: Which Should You Choose?
Choosing between GPT-5 nano and o1 depends on your priorities: cost efficiency, context length, or raw capability. GPT-5 nano is the more affordable option at $0.05/1M input tokens — 100% cheaper than o1. Meanwhile, o1 offers a significantly larger context window at 200,000 tokens vs 128,000 for GPT-5 nano.
These models target different tiers: GPT-5 nano is a efficient model while o1 is reasoning. This means they're optimized for different workloads. o1 targets more demanding workloads, while GPT-5 nano provides a cost-effective option for everyday tasks.
Output costs matter too. GPT-5 nano charges $0.40/1M output tokens vs $60.00 for o1. For generation-heavy workloads (content creation, code generation, summarization), output pricing often dominates your bill. GPT-5 nano has the edge here at $0.40/1M output tokens.
Best Use Cases
Choose GPT-5 nano when:
- • Budget is a primary concern
- • You're already using OpenAI's API ecosystem
- • You're running high-volume, latency-sensitive workloads
Choose o1 when:
- • You need a larger context window (200,000 tokens)
- • You need more capabilities (reasoning)
- • You need longer outputs (up to 65,536 tokens)
- • You're already using OpenAI's API ecosystem
Try Different Scenarios
Use the calculator below to see how costs change with different usage patterns
GPT-5 nano (OpenAI)
o1 (OpenAI)
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