Command R vs Gemma 4 26B A4B
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 Gemma 4 26B A4B.
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.
Gemma 4 26B A4B
Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind. Despite 25.2B total parameters, only 3.8B activate per token during inference โ delivering near-31B quality at...
Technical Specifications
| Specification | Command R | Gemma 4 26B A4B |
|---|---|---|
| Provider | Cohere | |
| Context Window | 128,000 tokens | 262,144 tokens |
| Agent Suitability | 78/100 | N/A |
| Time to First Token (TTFT) | 200 ms | N/A |
| Deployment Model | managed api | managed api |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2024-03-11 | 2026-04-03 |
API Pricing Comparison
Input Price per Million Tokens
Command R
$0.15
Gemma 4 26B A4B
$0.06
Output Price per Million Tokens
Command R
$0.60
Gemma 4 26B A4B
$0.33
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
- โธCost-effective RAG model โ strong multilingual search performance
- โธLimited agentic capability โ use Command R+ for complex multi-step tool use
Gemma 4 26B A4B Quirks & Gotchas
No developer gotchas reported.