Command R vs o3 Deep Research
Compare Cohere and OpenAI AI models
Cost Comparison (1000 input + 500 output tokens, 100 requests/day)
Command R
o3 Deep Research
Cost Differences
o3 Deep Research costs more than Command R
Feature Comparison
| Feature | Command R | o3 Deep Research |
|---|---|---|
| Provider | Cohere | OpenAI |
| Input Price | $0.15/1M tokens | $10.00/1M tokens |
| Output Price | $0.60/1M tokens | $40.00/1M tokens |
| Context Window | 128,000 tokens | 200,000 tokens |
| Max Output | 4,096 tokens | 32,768 tokens |
| Category | efficient | reasoning |
| Capabilities | textcode | textreasoningvisioncode |
| Release Date | 3/11/2024 | 6/26/2025 |
Command R vs o3 Deep Research: Which Should You Choose?
Choosing between Command R and o3 Deep Research depends on your priorities: cost efficiency, context length, or raw capability. Command R is the more affordable option at $0.15/1M input tokens — 99% cheaper than o3 Deep Research. Meanwhile, o3 Deep Research offers a significantly larger context window at 200,000 tokens vs 128,000 for 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 efficient model while o3 Deep Research is reasoning. This means they're optimized for different workloads. o3 Deep Research targets more demanding workloads, while Command R provides a cost-effective option for everyday tasks.
Output costs matter too. Command R charges $0.60/1M output tokens vs $40.00 for o3 Deep Research. 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.
Multimodal capabilities: o3 Deep Research supports vision (image inputs) while Command R is text-only. If your application needs image understanding, this narrows your choice.
Best Use Cases
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
Choose o3 Deep Research when:
- • You need a larger context window (200,000 tokens)
- • You need more capabilities (reasoning, vision)
- • You need longer outputs (up to 32,768 tokens)
- • You're already using OpenAI's API ecosystem
Try Different Scenarios
Use the calculator below to see how costs change with different usage patterns
Command R (Cohere)
o3 Deep Research (OpenAI)
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