Command R+ vs GPT-5 nano
Compare Cohere and OpenAI AI models
Cost Comparison (1000 input + 500 output tokens, 100 requests/day)
Command R+
GPT-5 nano
Cost Differences
GPT-5 nano costs less than Command R+
Feature Comparison
| Feature | Command R+ | GPT-5 nano |
|---|---|---|
| Provider | Cohere | OpenAI |
| Input Price | $2.50/1M tokens | $0.05/1M tokens |
| Output Price | $10.00/1M tokens | $0.40/1M tokens |
| Context Window | 128,000 tokens | 128,000 tokens |
| Max Output | 4,096 tokens | 8,192 tokens |
| Category | flagship | efficient |
| Capabilities | textcodereasoning | text |
| Release Date | 4/4/2024 | 8/7/2025 |
Command R+ vs GPT-5 nano: Which Should You Choose?
Choosing between Command R+ and GPT-5 nano depends on your priorities: cost efficiency, context length, or raw capability. GPT-5 nano is the more affordable option at $0.05/1M input tokens — 98% cheaper than Command R+.
These models come from different providers — Cohere and OpenAI — which means different API ecosystems, SDKs, rate limits, and terms of service. If you're already integrated with Cohere, switching to OpenAIinvolves migration effort beyond just pricing. Factor in your existing infrastructure when deciding.
These models target different tiers: Command R+ is a flagship model while GPT-5 nano is efficient. This means they're optimized for different workloads. Command R+ is built for complex tasks that require deeper reasoning, while GPT-5 nano offers better value for routine operations.
Output costs matter too. Command R+ charges $10.00/1M output tokens vs $0.40 for GPT-5 nano. For generation-heavy workloads (content creation, code generation, summarization), output pricing often dominates your bill. GPT-5 nano has the edge here at $0.40/1M output tokens.
Best Use Cases
Choose Command R+ when:
- • You need more capabilities (code, reasoning)
- • You're already using Cohere's API ecosystem
Choose GPT-5 nano when:
- • Budget is a primary concern
- • You need longer outputs (up to 8,192 tokens)
- • 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
Command R+ (Cohere)
GPT-5 nano (OpenAI)
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