GPT-5.5 vs GPT-4o Mini
Compare GPT-5.5 vs GPT-4o Mini API pricing, token costs, context windows, and latency. See which model is cheaper and better for your stack.
GPT-5.5 charges $5.00/1M input and $30.00/1M output tokens, compared to GPT-4o Mini at $0.15/1M input and $0.60/1M output. GPT-4o Mini is 33.3x cheaper on input tokens. In reasoning benchmarks, Neither rated holds the higher AA Intelligence Index rating. For latency-critical streaming, throughput figures are not yet measured for at least one of these models.
Full Metric & Specification Comparison
| Metric | GPT-5.5 | GPT-4o Mini | Advantage |
|---|---|---|---|
| Provider | OpenAI | OpenAI | - |
| Input Token Cost (1M) | $5.000 | $0.150 | GPT-4o Mini |
| Output Token Cost (1M) | $30.000 | $0.600 | GPT-4o Mini |
| Context Window | 922k tokens | 128k tokens | GPT-5.5 |
| AA Intelligence Index | Unrated | Unrated | Unrated |
| Streaming Latency | Moderate | Unrated | - |
Key Architectural Takeaways
- Input Token Cost: GPT-5.5 is $5.00/1M vs GPT-4o Mini at $0.15/1M
- Output Token Cost: GPT-5.5 is $30.00/1M vs GPT-4o Mini at $0.60/1M
- Context Window: GPT-5.5 supports 922k tokens vs GPT-4o Mini with 128k tokens
- Benchmark Intelligence Rating: not rated for one or both models
- Inference Latency: GPT-5.5 is rated Moderate vs GPT-4o Mini rated null
Calculate Your Team's Exact Bill Difference
Drag the sliders below to see real-time cost divergences based on your daily token consumption.
Deploying GPT-4o Mini over GPT-5.5 saves $293.25/mo ($3519/yr) at this volume.
Frequently Asked Questions
Is GPT-5.5 cheaper than GPT-4o Mini?
GPT-4o Mini is significantly more economical, charging $0.15/1M input compared to $5.00/1M for GPT-5.5.
Which model should I choose for production?
If your primary constraint is API cost and high query throughput, choose GPT-4o Mini. If you require peak reasoning accuracy and complex tool use, Neither rated is recommended.
How does context window compare between GPT-5.5 and GPT-4o Mini?
GPT-5.5 offers the larger context window (922k tokens), allowing you to pass significantly larger codebases or documents without chunking.
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