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Qwen 2.5 72B Example Reports

One of the most capable open-source models available, demonstrating exceptional performance across technical, academic, and policy research domains.

Model Details

  • Parameters: 72 Billion
  • Context: 131K tokens
  • Deployment: Self-hosted via vLLM
  • Best For: Complex research, technical analysis, policy papers

Available Reports

  • Breakthroughs in Superconductors & Quantum Computing

    Style: Popular science magazine
    Length: ~13,000 words

    Explores room-temperature superconductors, quantum computing advances, and next-gen EV batteries in an accessible format for armchair experts.

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  • Behavior-Elastic Demand Curves

    Style: Technical economic analysis
    Length: ~18,000 words

    Deep dive into neuro-marketing integration with demand elasticity models, featuring mathematical frameworks and empirical evidence.

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  • Algorithmic Decision Systems & Social Inequality

    Style: Comprehensive policy review
    Length: ~27,000 words

    Examines algorithmic bias across healthcare, education, and social services with detailed case studies and policy recommendations.

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  • Balancing Algorithmic Efficiency & Procedural Justice

    Style: Global governance analysis
    Length: ~15,000 words

    Analyzes the tension between computational efficiency and fairness in automated decision-making systems worldwide.

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Model Performance

Strengths

  • Superior Reasoning: Exceptional logical flow and argument construction
  • Technical Depth: Handles complex mathematical and scientific concepts with ease
  • Context Management: Maintains coherence across very long documents (100K+ tokens)
  • Citation Handling: Excellent at managing and formatting academic references
  • Multilingual: Strong performance across multiple languages

Best Use Cases

  • Academic research papers requiring deep analysis
  • Technical documentation with complex requirements
  • Policy papers needing comprehensive coverage
  • Long-form content with multiple interconnected sections
  • Reports requiring extensive citations and references

Deployment Configuration

python -m vllm.entrypoints.openai.api_server \
    --model "/path/to/model/Qwen_Qwen2.5-72B-Instruct-AWQ" \
    --tensor-parallel-size 4 \
    --port 5000 \
    --host 0.0.0.0 \
    --gpu-memory-utilization 0.9 \
    --served-model-name "localmodel" \
    --disable-log-requests \
    --disable-custom-all-reduce \
    --guided-decoding-backend "xgrammar" \
    --max-model-len 131000 \
    --speculative-config '{"model": "/path/to/model/Qwen_Qwen2.5-1.5B-Instruct-AWQ", "num_speculative_tokens": 5}'