Bench test · AI Coding
Sourcegraph Cody vs LLaMA
Same rack, same rubric, four independent agents. Here's how they measure up — and which we'd pick.
| Sourcegraph Cody | LLaMA | |
|---|---|---|
| consensus | score8.0/10 | score7.9/10 |
| agents won | 2 / 4 ▲ | 1 / 4 |
| from | Free | Free |
| free tier | yes | yes |
| category | AI Coding | AI Coding |
Agent panel — head to head
| Anthropic | 8.2 ▲ | 7.8 |
| OpenAI | 7.6 ▲ | 7.1 |
| Gemini | 8.3 | 8.8 ▲ |
| Grok | 7.8 | 7.8 |
Sourcegraph Cody
- ✓Superior context awareness across entire codebase
- ✓Reduces time on code comprehension and refactoring
- ✓Strong enterprise-grade security and privacy controls
- —Requires Sourcegraph instance setup for full functionality
- —Steeper learning curve compared to simpler assistants
- —Limited free tier compared to competitors
Codebase-aware code completion and generationSemantic code search and navigationAutomated refactoring and bug fixesMulti-file context understandingIDE and editor integrationsNatural language code explanations
LLaMA
- ✓Runs on consumer-grade hardware with good performance
- ✓Fully open-source enabling community contributions
- ✓Competitive results compared to larger proprietary models
- —Requires technical expertise for setup and deployment
- —Less refined than some commercial alternatives
- —License restrictions on commercial use (original version)
Multiple model sizes (7B to 65B parameters)Open-source and freely availableOptimized for inference efficiencyStrong coding and reasoning capabilitiesSupport for multiple programming languagesFine-tuning friendly architecture
Free · free tier
Try Sourcegraph Cody ▸Free · free tier
Try LLaMA ▸Verdict
Sourcegraph Cody takes it — 8 to 7.9 (a photo finish).
The panel gave Sourcegraph Cody the edge on 2 of 4 agents. It's close enough that LLaMA is a fair pick if it fits your workflow better.