Claude 3.5 Sonnet vs GPT-4o: Code Generation Showdown
We ran 47 identical coding prompts through both models and measured accuracy, speed, and cost. The results surprised us.
Please wait while we prepare your content.
An independent lab for testing tools, models, and workflows.
We publish what we find.
Honest, detailed reviews of AI tools and platforms. No affiliate fluff.
Clear guides on models, concepts, and workflows. Built for practitioners.
Things we built, shipped, or broke. Real projects with real takeaways.
Test and evaluate AI tools, models, APIs. Systematic, reproducible assessments with clear methodologies.
OngoingPublish findings as blogs, videos, and livestreams. Making complex AI accessible to everyone.
ActiveShip our own AI-powered products. From internal tools to public-facing applications.
In ProgressLimited consulting and business training. Helping teams understand and adopt AI effectively.
BookingWe ran 47 identical coding prompts through both models and measured accuracy, speed, and cost. The results surprised us.
After debugging 12 production RAG systems, we identified the three most common failure patterns and their fixes.
From zero to a working voice assistant in 48 hours. Here is every decision we made, every mistake, and what worked.
A team of specialized AI agents can process, extract, and summarize complex legal documents 10x faster than a single LLM pass with higher accuracy.
CrewAI framework, GPT-4o for extraction, Claude for summarization, custom validation agent
A fine-tuned GPT-3.5 can match GPT-4 prompt-engineered performance on domain-specific classification at 1/10th the cost.
5,000 labeled samples, OpenAI fine-tuning API, evaluation on held-out test set of 1,000