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

Devin vs Code Llama

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

DevinCode Llama
consensus
score7.6/10
score7.9/10
agents won2 / 42 / 4
fromCustomCustom
free tiernono
categoryAI CodingAI Coding

Agent panel — head to head

Anthropic7.87.2
OpenAI8.57.5
Gemini7.28.9
Grok7.07.8

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

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

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Custom · no free tier

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Verdict

Code Llama takes it — 7.9 to 7.6 (a photo finish).

The panel gave Code Llama the edge on 2 of 4 agents. It's close enough that Devin is a fair pick if it fits your workflow better.