Model Comparison
DeepSeek-R1 vs Command R+Which is better in 2026?
Comparing DeepSeek-R1 and Command R+ across benchmarks, pricing, and capabilities.
Verdict: DeepSeek-R1 vs Command R+ — which is better?
DeepSeek-R1 (by DeepSeek) and Command R+ (by Cohere) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
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.
Choose DeepSeek-R1 if…
- you process long inputs — it offers a 131,072 token context window
- you want the most recent training data — it shipped Jan 2025
Choose Command R+ if…
- cost matters — it's about 2.2x cheaper per token
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-R1 and Command R+don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-R1 ($0.55/1M tokens) is 2.2x more expensive than Command R+ ($0.25/1M tokens).
For output processing, DeepSeek-R1 ($2.19/1M tokens) is 2.2x more expensive than Command R+ ($1.00/1M 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
DeepSeek-R1 is licensed under MIT, while Command R+ uses CC BY-NC.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
CC BY-NC
Open weights
Release Timeline
When each model was launched
DeepSeek-R1 was released on 2025-01-20, while Command R+ was released on 2024-08-30.
DeepSeek-R1 is 5 months newer than Command R+.
Jan 20, 2025
1.4 years ago
4mo newerAug 30, 2024
1.8 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-R1 is available from DeepSeek, DeepInfra, Together, Fireworks. Command R+ is available from Cohere, Bedrock.
DeepSeek-R1
Command R+
Outputs Comparison
Key Takeaways
DeepSeek-R1
View detailsDeepSeek
Command R+
View detailsCohere
Detailed Comparison
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FAQ
Common questions about DeepSeek-R1 vs Command R+.