GPT-4o mini vs GPT-5.1
Detailed pricing comparison and cost analysis.
Updated September 2026
Cost Simulator
| Feature | GPT-4o mini | GPT-5.1 |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Input Price (1M) | $0.15 | $1.25 |
| Output Price (1M) | $0.60 | $10.00 |
| Context Window | 128,000 | 400,000 |
Verdict
GPT-4o mini costs $0.15 per 1M input tokens and $0.60 per 1M output tokens. GPT-5.1 costs $1.25 per 1M input tokens and $10.00 per 1M output tokens. GPT-4o mini is 88% cheaper on input tokens than GPT-5.1. For output tokens, GPT-4o mini is the more affordable option at $0.60/1M vs $10.00.
On context window, GPT-5.1 supports 400,000 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.
When to choose GPT-4o mini
- ✓ You need the lowest input token cost ($ 0.15/1M)
- ✓ Your workload is output-heavy — GPT-4o mini generates text cheaper
- ✓ You are already integrated with OpenAI
When to choose GPT-5.1
- ✓ You need a larger context window (400,000 tokens)
- ✓ 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-4o mini cheaper than GPT-5.1? ▼
GPT-4o mini is cheaper on input tokens at $0.15/1M vs $1.25/1M for GPT-5.1 — a 88% saving.
What is the context window of GPT-4o mini vs GPT-5.1? ▼
GPT-4o mini has a 128,000-token context window. GPT-5.1 has a 400,000-token context window. GPT-5.1 supports the larger context, suitable for longer documents and agentic workflows.
Which model is better: GPT-4o mini or GPT-5.1? ▼
The best choice depends on your use case. For cost efficiency on input tokens, GPT-4o mini is the cheaper option. For maximum context length, GPT-5.1 supports 400,000 tokens. Use the comparison table above to find the right fit for your workload.