GPT-5 nano vs o4-mini Deep Research
GPT-5 nano vs o4-mini Deep Research: GPT-5 nano is cheaper for input-heavy usage ($0.05/M vs $2.00/M input tokens), while o4-mini Deep Research is better for long-context tasks (200,000 tokens).
Direct answer: choose GPT-5 nano for lower token spend and choose o4-mini Deep Research when your workload needs longer context.
Compare input and output token pricing, context windows, and monthly cost estimates on one page so you can pick the cheaper model fast.
Cost Comparison (1000 input + 500 output tokens, 100 requests/day)
GPT-5 nano
o4-mini Deep Research
Cost Differences
o4-mini Deep Research costs more than GPT-5 nano
Quick Recommendation
Winner for direct API pricing: GPT-5 nano. At the default workload, GPT-5 nano saves about $17.25/month ($209.875/year) versus o4-mini Deep Research.
Feature Comparison
| Feature | GPT-5 nano | o4-mini Deep Research |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Input Price | $0.05/1M tokens | $2.00/1M tokens |
| Output Price | $0.40/1M tokens | $8.00/1M tokens |
| Context Window | 128,000 tokens | 200,000 tokens |
| Max Output | 8,192 tokens | 32,768 tokens |
| Category | efficient | reasoning |
| Capabilities | text | textreasoningcode |
| Release Date | 8/7/2025 | 6/26/2025 |
GPT-5 nano vs o4-mini Deep Research: Which Should You Choose?
Choosing between GPT-5 nano and o4-mini Deep Research 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 — 98% cheaper than o4-mini Deep Research. Meanwhile, o4-mini Deep Research 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 o4-mini Deep Research is reasoning. This means they're optimized for different workloads. o4-mini Deep Research 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 $8.00 for o4-mini Deep Research. 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 o4-mini Deep Research when:
- • You need a larger context window (200,000 tokens)
- • You need more capabilities (reasoning, code)
- • You need longer outputs (up to 32,768 tokens)
- • You're already using OpenAI's API ecosystem
Pros and Caveats at a Glance
GPT-5 nano
- • Input pricing: $0.05/M tokens
- • Output pricing: $0.40/M tokens
- • Context window: 128,000 tokens
- • Max output: 8,192 tokens
Watch out for
- • Smaller context window than o4-mini Deep Research
o4-mini Deep Research
- • Input pricing: $2.00/M tokens
- • Output pricing: $8.00/M tokens
- • Context window: 200,000 tokens
- • Max output: 32,768 tokens
Watch out for
- • Higher input cost than GPT-5 nano
- • Higher output cost than GPT-5 nano
Try Different Scenarios
Use the calculator below to see how costs change with different usage patterns
GPT-5 nano (OpenAI)
o4-mini Deep Research (OpenAI)
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