alt Hacker NewsAs other people are saying here: the Gemini models are mostly terrible at tool use and long context management. And maybe not quite as good with finicky "detail" parts of coding generally.
Where they excel is just total holistic _knowledge_ about the world. I don't like "talking" to it, because I kind of hate its tone, but I find Gemini generally extremely useful for research and analysis tasks and looking up information.
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CuriouslyC • yesterday at 6:31 PM
Gemini had the best long context support for the longest time, and even now at >400k tokens it's still got the best long context recall.
Gemini is just not trained for autonomy/tool use/agentic behavior to the same degree as the other frontier models. Goog seems to emphasize video/images/scientific+world knowledge.
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People who say Gemini is bad at long contexts are so wrong.
You can put whole 50,000 - 70,000 LOC codebase into Gemini 3.1 Pro context making it 800,000+ tokens, give it detailed task and ask for whole changed files back and it will execute it sometimes in one shot, sometimes in two. E.g depend on whatever stack you work with let you see all the errors at once so it can fix everything on single reply.
Yes it will give you back 5-15 files up to 4000 LOC total with only relevant parts changed.
This is terrible inefficient way to burn $10 of tokens in 20 minutes, but attention and 1:1 context retention is truly amazing.
PS: At the same time it is bad at tool use, but this have nothing to do with context.