GPT-4o (Omni) vs o3-mini (Reasoning)
Compare GPT-4o (Omni) vs o3-mini (Reasoning) API pricing, token costs, context windows, and latency. See which model is cheaper and better for your stack.
GPT-4o (Omni) charges $2.50/1M input and $10.00/1M output tokens, compared to o3-mini (Reasoning) at $1.10/1M input and $4.40/1M output. o3-mini (Reasoning) is 2.3x cheaper on input tokens. In benchmark reasoning, o3-mini (Reasoning) holds the higher intelligence rating (93/100). For latency-critical streaming, GPT-4o (Omni) delivers 90 t/s (420ms TTFT) while o3-mini (Reasoning) provides 95 t/s (580ms TTFT).
Full Metric & Specification Comparison
| Metric | GPT-4o (Omni) | o3-mini (Reasoning) | Advantage |
|---|---|---|---|
| Provider | OpenAI | OpenAI | - |
| Input Token Cost (1M) | $2.500 | $1.100 | o3-mini (Reasoning) |
| Output Token Cost (1M) | $10.000 | $4.400 | o3-mini (Reasoning) |
| Context Window | 128k tokens | 200k tokens | o3-mini (Reasoning) |
| Intelligence Benchmark Score | 92/100 | 93/100 | o3-mini (Reasoning) |
| Streaming Latency | Fast | Fast | - |
Key Architectural Takeaways
- Input Token Cost: GPT-4o (Omni) is $2.50/1M vs o3-mini (Reasoning) at $1.10/1M
- Output Token Cost: GPT-4o (Omni) is $10.00/1M vs o3-mini (Reasoning) at $4.40/1M
- Context Window: GPT-4o (Omni) supports 128k tokens vs o3-mini (Reasoning) with 200k tokens
- Benchmark Intelligence Rating: GPT-4o (Omni) scores 92/100 vs o3-mini (Reasoning) at 93/100
- Inference Latency: GPT-4o (Omni) is rated Fast vs o3-mini (Reasoning) rated Fast
Calculate Your Team's Exact Bill Difference
Drag the sliders below to see real-time cost divergences based on your daily token consumption.
Deploying o3-mini (Reasoning) over GPT-4o (Omni) saves $63.00/mo ($756/yr) at this volume.
Frequently Asked Questions
Is GPT-4o (Omni) cheaper than o3-mini (Reasoning)?
o3-mini (Reasoning) is significantly more economical, charging $1.10/1M input compared to $2.50/1M for GPT-4o (Omni).
Which model should I choose for production?
If your primary constraint is API cost and high query throughput, choose o3-mini (Reasoning). If you require peak reasoning accuracy and complex tool use, o3-mini (Reasoning) is recommended.
How does context window compare between GPT-4o (Omni) and o3-mini (Reasoning)?
o3-mini (Reasoning) offers the larger context window (200k tokens), allowing you to pass significantly larger codebases or documents without chunking.
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