Command R vs Gemini 2.5 Pro
How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Command R and Gemini 2.5 Pro.
Command R
Command R is Cohere's lightweight, cost-efficient model engineered for high-speed enterprise integrations, productivity automation, and retrieval-augmented generation (RAG) pipelines. Optimized for low-latency API tool use and structured JSON output, it is particularly effective in enterprise search and question-answering systems where fast, reliable responses are critical. With a 128,000-token context window and a price of $0.15/MTok for input, Command R provides strong RAG performance and multilingual support at a fraction of the cost of Command R+, making it the preferred choice for teams scaling intelligent document retrieval at high request volumes.
Gemini 2.5 Pro
Gemini 2.5 Pro is Google’s state-of-the-art AI model designed for advanced reasoning, coding, mathematics, and scientific tasks. It employs “thinking” capabilities, enabling it to reason through responses with enhanced accuracy...
Technical Specifications
| Specification | Command R | Gemini 2.5 Pro |
|---|---|---|
| Provider | Cohere | |
| Context Window | 128,000 tokens | 1,048,576 tokens |
| Agent Suitability | 78/100 | 90/100 |
| Time to First Token (TTFT) | 200 ms | 450 ms |
| Deployment Model | managed api | managed api |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2024-03-11 | 2025-06-17 |
API Pricing Comparison
Input Price per Million Tokens
Command R
$0.15
Gemini 2.5 Pro
$1.25
Output Price per Million Tokens
Command R
$0.60
Gemini 2.5 Pro
$10.00
Want to test both models live?
Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.
Benchmark Performance Metrics
Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.
Command R Quirks & Gotchas
- ▸Cost-effective RAG model — strong multilingual search performance
- ▸Limited agentic capability — use Command R+ for complex multi-step tool use
Gemini 2.5 Pro Quirks & Gotchas
- ▸Legacy model — migrate to Gemini 3.1 Pro for better tool calling and lower latency