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

LLaMA Code Models vs Continue

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

LLaMA Code ModelsContinue
consensus
score8.6/10
score8.6/10
agents won1 / 41 / 4
fromCustomCustom
free tiernono
categoryAI CodingAI Coding

Agent panel — head to head

Anthropic7.88.2
OpenAI8.58.5
Gemini9.59.0
Grok8.58.5

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

Continue

  • Open-source and privacy-focused
  • Works offline with local models
  • Flexible integration with multiple AI providers
  • Requires manual setup and configuration
  • Performance depends on selected model quality
  • Smaller community compared to GitHub Copilot
AI code completion and generationSupport for multiple LLM providersLocal and cloud model optionsCode refactoring and documentationChat-based code assistanceCustomizable prompts and workflows

Custom · no free tier

Try LLaMA Code Models

Custom · no free tier

Try Continue

Verdict

Dead heat — both land at 8.6. Pick on price and fit.