Codex Mini vs Command R
Compare OpenAI and Cohere AI models
Cost Comparison (1000 input + 500 output tokens, 100 requests/day)
Codex Mini
Command R
Cost Differences
Command R costs less than Codex Mini
Feature Comparison
| Feature | Codex Mini | Command R |
|---|---|---|
| Provider | OpenAI | Cohere |
| 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 | 4,096 tokens |
| Category | efficient | efficient |
| Capabilities | textcodereasoning | textcode |
| Release Date | 2/2/2026 | 3/11/2024 |
Codex Mini vs Command R: Which Should You Choose?
Choosing between Codex Mini and Command R depends on your priorities: cost efficiency, context length, or raw capability. Command R 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 Command R.
These models come from different providers — OpenAI and Cohere — which means different API ecosystems, SDKs, rate limits, and terms of service. If you're already integrated with OpenAI, switching to Cohereinvolves migration effort beyond just pricing. Factor in your existing infrastructure when deciding.
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: Command R 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 Command R. For generation-heavy workloads (content creation, code generation, summarization), output pricing often dominates your bill. Command R has the edge here at $0.60/1M output tokens.
Best Use Cases
Choose Codex Mini when:
- • You need a larger context window (200,000 tokens)
- • You need more capabilities (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 Command R when:
- • Budget is a primary concern
- • You're already using Cohere'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)
Command R (Cohere)
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