The AI agent space right now feels like it’s all Codex and Claude. Anyone using agents seems to dismiss Gemini to some degree.
But Gemini has four use cases where other models genuinely cannot compete.
1. Bulk Data Cleaning — Flash Lite Is Unmatched on Cost
For long-context work and bulk data cleaning, Flash Lite offers the best cost-to-performance ratio among non-Chinese closed-source models. If you don’t trust Chinese API endpoints, don’t want to route through OpenRouter, and can’t run local models, Gemini is one of your best options.
2. Audio Multimodal — It Understands Music
Gemini’s audio processing goes beyond speech-to-text. It handles multiple speakers, recognizes tone, and can even pinpoint the exact positions of choruses and bridges in music.
I once experimented with using Strudel for song transitions, having Gemini identify segment boundaries in music tracks. The accuracy was remarkably high. This capability is something neither Claude nor GPT can do today.
3. Video Understanding — One Step, Not Frame-by-Frame
A student of mine needed to sift through a large collection of family vacation videos, keeping clips with family members and discarding footage of pure scenery and strangers.
With Claude, this would require extracting frames one by one and running image recognition on each — a tedious pipeline. Gemini can process the video directly and mark which segments contain the target people.
4. Book Scanning OCR — Coordinates Included
Another student needed to digitize scanned books. Claude’s recognition accuracy drops for non-Latin scripts, and its handling of embedded figures is mediocre.
Gemini not only reads text in images accurately but also returns the coordinates of each element within the image, enabling programmatic extraction. This is incredibly useful for building book digitization pipelines.
Bottom Line
People who dismiss Gemini outright usually haven’t seen enough use cases. Every model has its sweet spot. Choosing tools isn’t about picking sides.