DeepSeek-R1 is a 671B parameter Mixture-of-Experts (MoE) model with 37B activated parameters per token, trained via large-scale reinforcement learning with a focus on reasoning capabilities. It incorporates two RL stages for discovering improved reasoning patterns and aligning with human preferences, along with two SFT stages for seeding reasoning and non-reasoning capabilities. The model achieves performance comparable to OpenAI-o1 across math, code, and reasoning tasks.
Command R+ is Cohere’s cutting-edge generative AI model, engineered for enterprise-grade performance where speed, security, and output quality are critical. Designed to run efficiently with minimal infrastructure, it outperforms top-tier models like GPT-4o and DeepSeek-V3 in both capability and cost-effectiveness. Featuring an extended 256K token context window—twice as large as most leading models—it excels at complex multilingual and agent-based tasks essential for modern business operations. Despite its power, it can be deployed on just two GPUs, making it highly accessible. With blazing-fast throughput of up to 156 tokens per second—about 1.75x faster than GPT-4o—Command R+ delivers exceptional efficiency without compromising accuracy or depth.
| DeepSeek-R1 | Command A | |
|---|---|---|
Web Site
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Provider
| ||
Chat
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Release Date
| ||
Modalities
| text | text |
API Providers
| DeepSeek, HuggingFace | Cohere, Hugging Face, Major cloud providers |
Knowledge Cut-off Date
| Unknown | - |
Open Source
| Yes | Yes |
Pricing Input
| $0.55 per million tokens | $2.50 per million tokens |
Pricing Output
| $2.19 per million tokens | $10.00 per million tokens |
MMLU
| 90.8% Pass@1 Source | 85.5% Source |
MMLU-Pro
| 84% EM Source | Not available |
MMMU
| - | Not available |
HellaSwag
| - | Not available |
HumanEval
| - | Not available |
MATH
| - | 80% Source |
GPQA
| 71.5% Pass@1 Source | 50.8% Source |
IFEval
| 83.3% Prompt Strict Source | 90.9% Source |
SimpleQA
| - | - |
AIME 2024 | - | - |
AIME 2025 | - | - |
Aider Polyglot
| - | - |
LiveCodeBench v5
| - | - |
Global MMLU (Lite)
| - | - |
MathVista
| - | - |
Mobile Application | - |
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