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Do local code gen llms do better than cloud ai ed

Based on the search results and current benchmarks, here's a clear comparison:

Performance Reality

Cloud Models Still Lead

  • GPT-4 and Claude generally outperform local LLMs for code generation[6][7]
  • Cloud models offer superior accuracy and more sophisticated responses
  • Local models can approach GPT-3.5 level but don't match GPT-4[6]

DeepSeek Coder V2 Specifics

Advantages

  • The 15.7B Lite version would run well on your hardware
  • Supports 338 programming languages
  • Achieves 81.1% on HumanEval benchmark[5]
  • Zero cost and complete privacy

Disadvantages

  • Still falls short of GPT-4's capabilities
  • May require more prompting to get optimal results
  • Limited context compared to cloud models

Practical Recommendation

For Python code generation:

  • Use cloud models (GPT-4, Claude) when accuracy is critical
  • Use DeepSeek Coder V2 Lite locally when:
  • You need privacy
  • You want zero cost
  • You need offline capability
  • Quick iterations are important

The reality is that while local models like DeepSeek Coder V2 are impressive, they still don't match the sophistication of top cloud models for code generation[7]. However, they can be very useful as complementary tools, especially when privacy or cost is a concern.