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

LLaMA Code Models vs Devin

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

LLaMA Code ModelsDevin
consensus
score8.2/10
score8.2/10
agents won2 / 41 / 4
fromCustomCustom
free tiernono
categoryAI CodingAI Coding

Agent panel — head to head

Anthropic7.28.2
OpenAI8.58.5
Gemini9.08.5
Grok8.27.5

LLaMA Code Models

  • Free and open-source with no licensing costs
  • Community support and active development
  • Can be self-hosted and customized
  • May require technical setup and infrastructure
  • Performance varies by model size and hardware
  • Smaller community compared to proprietary alternatives
Code generation and synthesisMulti-language programming supportOpen-source and customizableInference optimization for efficiencyIntegration with development environmentsFine-tuning capabilities

Devin

  • Significantly accelerates development cycles
  • Reduces manual coding time and human errors
  • Handles repetitive and boilerplate code generation
  • May struggle with highly complex or novel problem domains
  • Requires oversight to ensure code quality and security
  • Limited understanding of specific business logic nuances
Autonomous code writing and executionReal-time debugging and error fixingProject planning and task breakdownIntegration with development tools and repositoriesCollaborative pair programming with humansApplication deployment capabilities

Custom · no free tier

Try LLaMA Code Models

Custom · no free tier

Try Devin

Verdict

Dead heat — both land at 8.2. Pick on price and fit.