alt Hacker NewsThey need to release benchmarks against Luna/Terra. Luna is much cheaper which feels like it undercuts the need for Flash.
I've always considered the Flash series of models to be for low-cost, high-volume, mostly text-based use cases (e.g. summarization, parsing, formatting), emphasis on low-cost.
[edit: ah, benchmarks here: https://blog.google/innovation-and-ai/models-and-research/ge...
more of a Terra than Luna competitor which is an interesting positioning. I feel like differentiation at the mid-tier of models is pretty difficult.]
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They compared against 5.6-terra on the model card: https://deepmind.google/models/model-cards/gemini-3-7-flash/
gemini flash is probably the best model for visual tasks right now. they also make it really easy to ingest videos
Matched roughly with Sol on DeepSwe cost per task.
Luna way cheaper. DeepSeek used to be, but I think it's somewhere on Sol's curve after the price hike.
Why is Gemini represented by points on this cost-quality plane, while competitor's models are represented by curves?
flash-lite is more of their luna tier competitor but even still not quite there yet, but gemini's dominance on multimodal and image understanding i think really gets downplayed on this site when most people think the only think you can do with LLMs is write code