Independently agent-testedAnthropic · OpenAI · Gemini · Grok
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Bench test · AI Coding

LLaMA Code vs Code Llama

Same rack, same rubric, four independent agents. Here's how they measure up — and which we'd pick.

LLaMA CodeCode Llama
consensus
score7.7/10
score7.9/10
agents won2 / 41 / 4
fromCustomCustom
free tiernono
categoryAI CodingAI Coding

Agent panel — head to head

Anthropic7.27.2
OpenAI8.27.5
Gemini9.08.9
Grok6.57.8

LLaMA Code

  • No licensing fees or usage costs
  • Can be self-hosted and modified
  • Respects privacy with local deployment
  • Requires significant computational resources
  • May produce less accurate results than proprietary models
  • Needs technical expertise to set up and optimize
Multi-language code generationCode completion and suggestionsOpen-source and freely availableCustomizable and fine-tunableRuns locally without cloud dependencyContext-aware programming assistance

Code Llama

  • Open-source and freely available for commercial use
  • Strong performance on diverse programming languages
  • Efficient smaller models suitable for edge deployment
  • Requires computational resources for local deployment
  • May produce lower quality output than proprietary models like GPT-4
  • Limited real-time training updates compared to closed-source alternatives
Multi-language code generationCode completion and infillingNatural language to code conversionBug detection and debugging assistanceAvailable in multiple model sizes (7B, 13B, 34B parameters)Instruction-following variants for conversational use

Custom · no free tier

Try LLaMA Code

Custom · no free tier

Try Code Llama

Verdict

Code Llama takes it — 7.9 to 7.7 (a photo finish).

The panel gave Code Llama the edge on 1 of 4 agents. It's close enough that LLaMA Code is a fair pick if it fits your workflow better.