Building with Gemini API: First Impressions vs Claude
Both are capable. The differences show up in the details — context windows, tool use reliability, and how each handles ambiguity.
I've been building AI-assisted features for a few months now, mostly with Claude via the API. Recently I integrated Gemini for a side project and noticed some meaningful differences.
Context Window
Gemini 1.5 Pro's 1M token context is genuinely useful when you need to pass in a full codebase. I ran an experiment: feeding an entire Node.js service (~8k lines) and asking it to find potential race conditions. It surfaced three I hadn't seen.
Claude's context is smaller but I've found it handles the edges of long contexts more reliably — less likely to "forget" instructions set early in the prompt.
Tool Use
This is where I spend the most time. Both support function calling, but in my testing Claude's tool use is more predictable — it calls tools when it should and doesn't fabricate return values when uncertain.
Gemini occasionally over-calls. Give it a search tool and it will search for things it probably already knows.
Code Generation Quality
Roughly equivalent for most tasks. Gemini slightly edges out on Kotlin and Java in my experience — possibly the training data. Claude feels stronger at reasoning about architecture and explaining tradeoffs.
My setup now
I've started using them for different tasks: Gemini for large-context sweeps and document processing; Claude for interactive pair programming and code review. They complement more than they compete.
The best model is increasingly "the right model for the job."