GPT-5.4 mini vs o3-mini
Detailed pricing comparison and cost analysis.
Updated September 2026
Cost Simulator
| Feature | GPT-5.4 mini | o3-mini |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Input Price (1M) | $0.75 | $1.10 |
| Output Price (1M) | $4.50 | $4.40 |
| Context Window | 400,000 | 200,000 |
Verdict
GPT-5.4 mini costs $0.75 per 1M input tokens and $4.50 per 1M output tokens. o3-mini costs $1.10 per 1M input tokens and $4.40 per 1M output tokens. GPT-5.4 mini is 32% cheaper on input tokens than o3-mini. For output tokens, o3-mini is the more affordable option at $4.40/1M vs $4.50.
On context window, GPT-5.4 mini supports 400,000 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.
When to choose GPT-5.4 mini
- ✓ You need the lowest input token cost ($ 0.75/1M)
- ✓ You need a larger context window (400,000 tokens)
- ✓ You are already integrated with OpenAI
When to choose o3-mini
- ✓ Your workload is output-heavy — o3-mini generates text cheaper
- ✓ You are already integrated with OpenAI
Use the calculator above to simulate your specific workload and find the exact break-even point. For most applications, the cheapest model is the one that minimises your total monthly bill given your input-to-output token ratio.
Frequently Asked Questions
Is GPT-5.4 mini cheaper than o3-mini? ▼
GPT-5.4 mini is cheaper on input tokens at $0.75/1M vs $1.10/1M for o3-mini — a 32% saving.
What is the context window of GPT-5.4 mini vs o3-mini? ▼
GPT-5.4 mini has a 400,000-token context window. o3-mini has a 200,000-token context window. GPT-5.4 mini supports the larger context, suitable for longer documents and agentic workflows.
Which model is better: GPT-5.4 mini or o3-mini? ▼
The best choice depends on your use case. For cost efficiency on input tokens, GPT-5.4 mini is the cheaper option. For maximum context length, GPT-5.4 mini supports 400,000 tokens. Use the comparison table above to find the right fit for your workload.