Command R+
Language Available Full comparison ↗ cohere/command-r-plus · by Cohere
· decoder-only-transformer
Pricing — 1 offering(s)
About this offering: Cohere Command R+ (08-2024). Optimised for enterprise RAG and tool-use pipelines. 128K context window. Includes native tool use and grounding capabilities.
Input tokens
- $2.50 / 1M tokens (input) Historical 2024-08-01 → 2026-06-15
- $2.50 / 1M tokens (input)
Historical
2026-06-16 → 2026-09-19
Correction
Corrected 2026-09-25: Modelglass first recorded a wrong price for these dates; this row replaces it, and the…
Corrected 2026-09-25: Modelglass first recorded a wrong price for these dates; this row replaces it, and the wrong row is no longer served.
- $2.50 / 1M tokens (input) Current 2026-09-20 → present
Output tokens
- $10.00 / 1M tokens (output) Historical 2024-08-01 → 2026-06-15
- $10.00 / 1M tokens (output)
Historical
2026-06-16 → 2026-09-19
Correction
Corrected 2026-09-25: Modelglass first recorded a wrong price for these dates; this row replaces it, and the…
Corrected 2026-09-25: Modelglass first recorded a wrong price for these dates; this row replaces it, and the wrong row is no longer served.
- $10.00 / 1M tokens (output) Current 2026-09-20 → present
Showing the active price and any recorded history. Full pricing history is available via the paid API — see API docs.
See how Command R+ fits into a cost-aware routing setup
See how →Capability profile
How Command R+ rates across core capability dimensions, with the task-level evidence behind each rating.
No coding benchmarks in Cohere's documentation for Command R+ (docs.cohere.com/docs/command-r-plus). No HumanEval, MBPP, or SWE-bench scores published. Consistent with registry capabilities.supports_coding unset.
Optimised for RAG with native grounding and citation features.
128K context.
Ratings are estimated — limited independent data is available for this model.
Operator guidance
Purpose-built for retrieval-augmented generation; strongest at tasks requiring native grounding and citations. Route here when Cohere's enterprise RAG features are specifically needed. Comparable pricing to GPT-4o and Command A.
Use cases
- Enterprise RAG pipelines with citation requirements
- Tool-use and function-calling workflows
- Grounded Q&A over private document corpora
Limitations
- Less capable than frontier models on pure reasoning without retrieval
- Capability ratings are qualitative, not a single cited benchmark run