DeepSeek-R1?

1

DeepSeek-R1 - GitHub

DeepSeek-R1 achieves performance comparable to OpenAI-o1 across m...

https://github.com/deepseek-ai/DeepSeek-R1

2

DeepSeek

DeepSeek-R1 is now live and open source, rivaling OpenAI's Model ...

https://www.deepseek.com/

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DeepSeek-R1 Release

DeepSeek-R1 Release. ⚡ Performance on par with OpenAI-o1. Fully o...

https://api-docs.deepseek.com/news/news250120

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DeepSeek-R1 vs OpenAI o1 benchmark comparisons

DeepSeek-R1 system requirements and local installation guide

DeepSeek-R1 MoE architecture technical details

DeepSeek-R1: Advanced Open-Source AI Reasoning Model

DeepSeek-R1 is an open-source AI model that matches OpenAI's o1 in performance while being 90-95% more cost-effective empire-icon1empire-icon3. Built on a Mixture-of-Experts (MoE) architecture with 671 billion parameters, the model activates only 37 billion parameters per inference, making it highly efficient empire-icon4.

Architecture and Technical Details

The model employs a sophisticated MoE architecture DeepSeek-V3 that enables selective parameter activation for each query empire-icon62. Key technical specifications include:

  • Total Parameters: 671 billion
  • Active Parameters: 37 billion per token
  • Context Length: Up to 128K tokens
  • Training Data: 14.8 trillion tokens empire-icon60

The model uses two key algorithms:

  1. R1-Zero: Trained purely through reinforcement learning without supervised fine-tuning
  2. R1: Incorporates both reinforcement learning and supervised fine-tuning for improved output quality empire-icon61

Performance Benchmarks

DeepSeek-R1 demonstrates impressive performance across various benchmarks empire-icon3:

  • AIME 2024: 79.8% (vs o1's 79.2%)
  • MATH-500: 97.3% (vs o1's 96.4%)
  • Codeforces Rating: 2,029 (better than 96.3% of human programmers)
  • MMLU: 90.8% (close to o1's 91.8%)

System Requirements and Installation

For local deployment, the hardware requirements vary based on model size empire-icon51:

Minimum Requirements:

  • GPU: NVIDIA GPU with 6GB+ VRAM for GPTQ version
  • RAM: 4GB for GGML/GGUF format
  • Storage: 200GB+ free space
  • OS: Windows 10/11 or Linux

Installation Steps:

  1. Install Ollama Ollama
  2. Download the appropriate model version:
# For 8GB VRAM
ollama run deepseek-r1
# For 12GB+ VRAM (higher quality)
ollama run deepseek-r1:16b-lite-instruct-q5_K_M

Access Options

DeepSeek-R1 can be accessed through multiple channels:

  1. Web Interface: Available at chat.deepseek.com with "DeepThink" mode

  2. API Access: Through platform.deepseek.com with competitive pricing:

    • Input Tokens (Cache Miss): $0.55 per million
    • Input Tokens (Cache Hit): $0.14 per million
    • Output Tokens: $2.19 per million empire-icon61
  3. Local Deployment: Available through Hugging Face under MIT license

Distilled Versions

DeepSeek has released six smaller, distilled versions of R1 for different computational requirements empire-icon3:

  • 1.5B parameters
  • 7B parameters
  • 8B parameters (Llama-based)
  • 14B parameters
  • 32B parameters
  • 70B parameters

These distilled models maintain impressive performance, with the 32B and 70B variants matching OpenAI's o1-mini in various benchmarks empire-icon43.

Limitations and Considerations

While powerful, users should be aware of certain limitations:

  • Language mixing issues in R1-Zero outputs
  • Chinese regulatory compliance requirements affecting certain topics
  • Higher computational requirements for full model deployment
  • Need for significant RAM and storage space for local installation empire-icon54

The model represents a significant advancement in open-source AI, offering comparable performance to proprietary solutions while maintaining accessibility and cost-effectiveness for the broader AI community empire-icon3empire-icon4.

write an outline for a paper about DESIGNING digital twin EXPERIMENTS: COMPARATIVE STUDIES ON A digital twin

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How to design and implement digital twin experiments using DeepSeek-R1 for comparative studies and performance analysis?

What are the computational requirements and hardware specifications needed for running large-scale digital twin simulations with DeepSeek-R1's 671B parameter model?

Designing Digital Twin Experiments: A Comparative Study Framework Using DeepSeek-R1

Digital twin experiments require careful design and robust computational infrastructure to ensure accurate comparative studies. The integration of DeepSeek-R1's advanced reasoning capabilities with digital twin simulations enables sophisticated analysis and real-time decision-making empire-icon1empire-icon7.

Experimental Design Framework

Infrastructure Requirements

For large-scale digital twin simulations using DeepSeek-R1's 671B parameter model, the following computational specifications are essential empire-icon2:

  • Base Hardware Configuration:
    • Multi-GPU setup with NVIDIA A100 80GB (×16 minimum)
    • High-speed NVMe SSDs for data storage
    • Minimum 1,342 GB VRAM for full model deployment
    • [(1)-^Ollama^-Enables efficient local

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What are the negative impacts of Elon Musk's Nazi salute controversy on Tesla's stock performance and shareholder value in comparison to other corporate digital twin simulation studies?

How do digital twin experiments and simulations help predict and analyze the impact of CEO behavior on company stock performance?

Impact négatif du "salut nazi" de Musk sur Tesla et ses actionnaires

La controverse du "salut nazi" d'Elon Musk lors de l'inauguration de Donald Trump en 2025 a eu des répercussions significatives sur Tesla et ses actionnaires. L'incident s'est produit lorsque Musk a fait un geste du bras tendu ressemblant au salut nazi lors d'un discours au Capital One Arena empire-icon1, suivi de blagues controversées sur les nazis et l'Holocauste sur X empire-icon2.

Réactions et Controverses

La situation s'est aggravée quand Musk a publié une série de jeux de mots faisant référence aux dirigeants nazis [(1)-^wrote^-Posts controversés sur X augmentant la

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Glass and Aluminium Sales Representative Positions in Johannesburg

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Current Vacancies

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  • Experience Required: 3-4 years
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  • Number of positions: 2
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Additional opportunities include positions at:

  • Phakisa Holdings Ltd - seeking sales-oriented professionals for a high-end glass & aluminium