Codex Mini vs GPT-4o mini
Compare OpenAI and OpenAI AI models
Cost Comparison (1000 input + 500 output tokens, 100 requests/day)
Codex Mini
GPT-4o mini
Cost Differences
GPT-4o mini costs less than Codex Mini
Feature Comparison
| Feature | Codex Mini | GPT-4o mini |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Input Price | $1.50/1M tokens | $0.15/1M tokens |
| Output Price | $6.00/1M tokens | $0.60/1M tokens |
| Context Window | 200,000 tokens | 128,000 tokens |
| Max Output | 32,768 tokens | 16,384 tokens |
| Category | efficient | efficient |
| Capabilities | textcodereasoning | textvision |
| Release Date | 2/2/2026 | 7/18/2024 |
Codex Mini vs GPT-4o mini: Which Should You Choose?
Choosing between Codex Mini and GPT-4o mini depends on your priorities: cost efficiency, context length, or raw capability. GPT-4o mini is the more affordable option at $0.15/1M input tokens — 90% cheaper than Codex Mini. Meanwhile, Codex Mini offers a significantly larger context window at 200,000 tokens vs 128,000 for GPT-4o mini.
Both models are in the efficient category, making this a direct head-to-head comparison. At scale — say 10,000 requests per day — the cost difference adds up: GPT-4o mini would save you roughly $1,215.00/month compared to Codex Mini. For startups and indie developers, that difference can be significant.
Output costs matter too. Codex Mini charges $6.00/1M output tokens vs $0.60 for GPT-4o mini. For generation-heavy workloads (content creation, code generation, summarization), output pricing often dominates your bill. GPT-4o mini has the edge here at $0.60/1M output tokens.
Multimodal capabilities: GPT-4o mini supports vision (image inputs) while Codex Mini is text-only. If your application needs image understanding, this narrows your choice.
Best Use Cases
Choose Codex Mini when:
- • You need a larger context window (200,000 tokens)
- • You need more capabilities (code, reasoning)
- • You need longer outputs (up to 32,768 tokens)
- • You're already using OpenAI's API ecosystem
- • You're running high-volume, latency-sensitive workloads
Choose GPT-4o mini when:
- • Budget is a primary concern
- • You're already using OpenAI's API ecosystem
- • You're running high-volume, latency-sensitive workloads
Try Different Scenarios
Use the calculator below to see how costs change with different usage patterns
Codex Mini (OpenAI)
GPT-4o mini (OpenAI)
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