Computer Benchmark Analysis Model (CBAM)

Benchmark Model

1. GPU Performance (30%)

   • 3DMark Time Spy
   • Unigine Superposition
   • Game-specific benchmarks (e.g., FPS in popular titles)

2. CPU Performance (25%)

   • Geekbench 6 (single-core and multi-core)
   • Cinebench R23
   • PassMark CPU

3. System Performance (20%)

   • PCMark 10
   • Storage speed (sequential and random read/write)
   • Thermal performance under load

4. RAM Performance (10%)

   • PassMark RAM
   • UserBenchmark RAM

5. Other Factors (15%)

   • Display quality (resolution, refresh rate, color accuracy)
   • Input devices (keyboard, touchpad, additional peripherals)
   • Software ecosystem and compatibility

Evaluation Methodology

1. Collect raw benchmark data for each component
2. Normalize scores within each category
3. Apply category weights to calculate Total Performance Score (TPS)
4. Calculate Performance Per $1000 (PPR) by dividing TPS by price in thousands
5. Generate visual representations of TPS and PPR using ASCII bar charts
6. Analyze strengths and weaknesses of each device
7. Identify target audiences based on device characteristics
8. Summarize key findings and top performers

Comparison Template

1. Header: Title, Date
2. Devices and Specifications Table
3. Performance Comparison Table:
   • Total Performance Score (TPS)
   • Performance Per $1000 (PPR)
4. TPS and PPR Visual Representations (ASCII bar charts)
5. Strengths and Weaknesses Table
6. Target Audience Recommendations
7. Conclusion: Key findings, top performers

Reporting Guidelines

• Use clear, concise language
• Maintain an unbiased, formal tone
• Employ Markdown formatting for improved readability
• Utilize headers, tables, and bullet points for organized presentation
• Include ASCII/Unicode visuals with color gradients (red to violet)
• Ensure bar lengths are proportional to represented values
• Highlight trade-offs in performance, security, build quality, display, value, and portability
• Cite sources using inline bracketed numbers

This comprehensive model provides a standardized approach for evaluating and comparing gaming devices, ensuring thorough and accurate assessments across various performance metrics and user-centric factors.

Citations:
[1] https://ppl-ai-file-upload.s3.amazonaws.com/web/direct-files/29190/7174f2e2-0800-473e-998b-14c9c9cc5b97/genAI-LLM-prompt_consolidate-raw-data.txt
[2] https://www.tomshardware.com/reviews/cpu-hierarchy,4312.html
[3] https://www.zachstechturf.com/gpucomparisons
[4] https://www.tomshardware.com/reviews/gpu-hierarchy,4388.html
[5] https://benchmarks.ul.com/compare/best-gpus
[6] https://www.reddit.com/r/pcmasterrace/comments/1csnp65/gpu_price_to_performance_comparison_20240515/