Best Computer for LLM: Apple or PC

Nvidia's Role in AI Computing

• Nvidia's dominance in AI computing is driven by hype but integrated GPUs (iGPUs) are gaining ground and proving to be efficient and cost-effective for most users.
• AMD's new chips offer high VRAM in affordable iGPUs, challenging Nvidia's expensive discrete GPUs.
• Nvidia is responding by releasing high-VRAM APUs, potentially impacting their dGPU market.
• Apple and AMD are showcasing that iGPUs can fulfill most computing needs effectively.

Nvidia vs. Mac for LLM Computing

• Nvidia offers high performance with setups like dual 3090s but may be pricier and less power-efficient.
• Mac Studio Ultra is efficient and can run large models, potentially being more future-proof with resale value.
• Nvidia may outperform Mac with EXL2 for certain models, but Mac offers advantages like low power consumption.

User Preferences

• Some users prefer both MacBook Pro and ThinkPad to avoid choosing one over the other.
• Others highlight the upgradability and performance of a PC for LLM computing needs.

Pros and Cons of Apple and PC for LLM Computing

Apple (MacBook Pro/Mac Studio Ultra)

• Pros:

  • Efficient and future-proof
  • Potentially better for larger models
  • Good resale value

• Cons:

  • Mac OS limitations for some users
  • Pricier than some PC alternatives

PC (with Nvidia GPUs)

• Pros:

  • High performance with setups like dual 3090s
  • Upgradability and customization

• Cons:

  • Higher power consumption
  • Less efficient than some Mac options

Overall Recommendation

• The choice between Apple (Mac) and PC (with Nvidia GPUs) for LLM computing depends on individual preferences and specific computing needs.
• Waiting for CES announcements could provide more insights to make an informed decision based on VRAM requirements, speed, efficiency, and pricing.