Command R+ vs DeepSeek-R1
Comparing Command R+ and DeepSeek-R1 across benchmarks, pricing, and capabilities.
Cohere · DeepSeek · Updated for 2026
Which is better?
Command R+ and DeepSeek-R1 trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, Command R+ is roughly 2.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-R1 also accepts a larger context window (131,072 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Command R+
- cost matters — it's about 2.2x cheaper per token
Choose DeepSeek-R1
- you process long inputs — it offers a 131,072 token context window
- you want the most recent training data — it shipped Jan 2025
At a glance
The differences that matter most.
Individual benchmarks
6 reported for Command R+ · 0 for DeepSeek-R1
Command R+ and DeepSeek-R1don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Command R+ ($0.25/1M tokens) is 2.2x cheaper than DeepSeek-R1 ($0.55/1M tokens).
For output processing, Command R+ ($1.00/1M tokens) is 2.2x cheaper than DeepSeek-R1 ($2.19/1M tokens).
In conclusion, DeepSeek-R1 is more expensive than Command R+.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-R1 has 567.0B more parameters than Command R+, making it 545.2% larger.
Context Window
Maximum input and output token capacity
DeepSeek-R1 accepts 131,072 input tokens compared to Command R+'s 128,000 tokens. DeepSeek-R1 can generate longer responses up to 131,072 tokens, while Command R+ is limited to 128,000 tokens.
License
Usage and distribution terms
Command R+ is licensed under CC BY-NC, while DeepSeek-R1 uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
CC BY-NC
Open weights
MIT
Open weights
Release Timeline
When each model was launched
Command R+ was released on 2024-08-30, while DeepSeek-R1 was released on 2025-01-20.
DeepSeek-R1 is 5 months newer than Command R+.
Aug 30, 2024
2.1 years ago
Jan 20, 2025
1.7 years ago
4mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Command R+ is available from Cohere, Bedrock. DeepSeek-R1 is available from DeepSeek, DeepInfra, Together, Fireworks.
Command R+
DeepSeek-R1
Outputs Comparison
Judge for yourself.
Run your own prompts against Command R+ and DeepSeek-R1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Command R+ vs DeepSeek-R1.