Most LLM benchmarks are useless for developers. They test things like "can it pass a bar exam" or "how does it score on MMLU" โ which tells you absolutely nothing about whether it will write good TypeScript or catch a subtle race condition in your async code.
This benchmark is different. We tested on tasks developers actually do: writing components, designing APIs, reviewing code, explaining complex errors, and reasoning through architectural decisions. The results surprised us in a few places.
200Coding Tasks
100Reasoning Tests
50Creative Prompts
01
Overall Scores
๐ค
Claude 3.5
Anthropic
9.6
out of 10
๐ Overall Winner
๐ฌ
ChatGPT-4o
OpenAI
8.8
out of 10
Best All-Rounder
๐ท
Gemini 1.5
Google
8.5
out of 10
Best Context
๐ฆ
Llama 3.1
Meta
8.2
out of 10
Best Free
Category Breakdown Chart
Recommended: 800ร360px ยท Grouped bar chart showing each model's score per category
02
Category Breakdown
| Category | Claude 3.5 | ChatGPT-4o | Gemini 1.5 | Llama 3.1 |
|---|---|---|---|---|
| TypeScript / Typing | ||||
| React Components | ||||
| System Design | ||||
| Debugging | ||||
| Response Speed | ||||
| Context Window | ||||
| Cost Efficiency |
03
The Honest Verdicts
๐ค Claude 3.5 Sonnet
Best for serious development work
Claude wins on everything that requires sustained reasoning: system design, TypeScript architecture, debugging complex issues. What separates it from the others is that it pushes back. Ask Claude to build something with a subtle flaw and it will flag the flaw before writing a line of code. No other model does this consistently. The tradeoff is it's slightly slower on simple tasks โ which barely matters when you're building real things.
๐ฌ ChatGPT-4o
Best for speed and mixed workflows
GPT-4o is faster than Claude on response generation and marginally better for tasks that mix coding with writing โ a technical blog post, a README with code examples, a product spec. Its GPTs ecosystem also gives it a practical advantage for specific use cases. Where it falls short is on deep TypeScript work and complex multi-file refactoring โ Claude pulls ahead noticeably there.
๐ท Gemini 1.5 Pro
Best for large codebase analysis
The 1M token context window is genuinely transformative for certain use cases. Need to analyse an entire legacy codebase and find security vulnerabilities? Gemini can hold the whole thing in memory simultaneously. For standard component and API work it's competitive but not quite at Claude's level. The free tier is unexpectedly good โ better than ChatGPT's free tier on most coding tasks.
๐ฆ Llama 3.1 405B
Best if you need privacy or free
The fact that this is genuinely competitive with GPT-4o on most coding tasks, and it's free, is remarkable. For teams with strict data privacy requirements, self-hosting Llama 3.1 is now a real option. The gap to Claude is meaningful on complex reasoning but smaller than you'd expect given the cost difference.
Testing Environment Screenshot
Recommended: 800ร280px ยท Screenshot of benchmark testing setup showing the same prompt across different tools
โก The Bottom Line
- For coding: Claude 3.5 โ no contest on TypeScript, system design and debugging
- For speed and all-round use: ChatGPT-4o โ faster, great for mixed workflows
- For large file analysis: Gemini 1.5 โ the 1M context window is a genuine differentiator
- For free / privacy: Llama 3.1 โ shockingly capable given the cost
- Most developers should have Claude + one other โ they're complementary, not competing
- Scores update monthly โ AI moves fast and a 3-month-old benchmark is ancient history
Read Next
AI Security Guide โ Prompt Injection, API Keys and Safe Coding
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