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by MrBuddyCasino23 hours ago |
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upvoteby bicx23 hours ago|
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Gemini is still my top choice within production software for typical data extraction from unstructured data. Gemini Flash Lite feels like a cheat code for speed, and it's really cheap.

Some other Chinese models are also fast and cheap, but a harder sell in a U.S. production environment.

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upvoteby ComputerGuru19 hours ago|
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Speaking from experience here, flash lite models have amazing price, speed, and perform far above their size, but are susceptible to very bad instruction following and recall when either complexity or context size inch up. They’ll just forget to apply your instructions to portions of the input, and repeat parts of the input that should be returned verbatim as direct quotes but with subtle changes (breaking urls, for example).
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upvoteby MrBuddyCasino19 hours ago|
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Yes you have to continuously tune the prompts ever so subtly. 3.5 is a lot better than than 3.1 tho.

Important to remember that json schema instructions take precedence over the normal prompt, so move as much into property descriptions as possible.

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upvoteby ComputerGuru18 hours ago|
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This was 3.5 flash lite, actually, and after prompt tuning. It was very clearly an issue that correlated with input (JSON array) size, the more elements in the batch, the higher the error rate.

3.0 flash (not lite) handled it like a champ though, fwiw.

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upvoteby MrBuddyCasino22 hours ago|
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Yeah Gemini 3.5 Flash Lite is really good. Which Chinese models can you recommend?
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upvoteby SkalskiP22 hours ago|
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Hi, I’m the author of this blog. It depends on how strong of a model you need, but in general, Qwen is easily the best among the Chinese models right now.

Over the last two weeks, Qwen released two new models. Qwen3.8-Max is totally insane, but it’s only available through the Alibaba Cloud API. I wrote a similar blog covering Qwen3.8-Max: [https://blog.roboflow.com/qwen3-8-max/](https://blog.roboflow.com/qwen3-8-max/)

If you’re looking for something you can run locally, Qwen3.8-27B might be a great option. On Friday, I did a quick comparison between Qwen3.8-Max and Qwen3.8-27B: [https://x.com/skalskip92/status/2088411215441621469?s=20](https://x.com/skalskip92/status/2088411215441621469?s=20)

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upvoteby kanemcgrath20 hours ago|
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Googles local gemma models which target roughly the same parameter count range, are known for being a lot better at vision tasks than qwen, no idea if 3.8 has changed that though
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upvoteby SkalskiP19 hours ago|
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Really? Gemma4-31B should be better than Qwen3.8-27B? I'm happy to test that.
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upvoteby b34522 hours ago|
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I've been using Qwen3.5-9B, hosted locally for PDF data extraction and it performs pretty well when extracting data from tables and infographics
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upvoteby msp2622 hours ago|
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[dead]
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upvoteby dannyw21 hours ago|
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Gemini is honestly an excellent LLM with many capability strengths.

For example, 3.7 Flash is #1 on MMLU Pro and AA’s agentic spreadsheets/docs benchmark, etc. Yes, beating Fable.

Agentic coding is only one dimension.

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upvoteby fau20 hours ago|
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Anecdotally, Gemini Flash is the leader for a particular use case of mine and has been since at least version 2.5. But now there's also Luna as the first real competitor thanks to the price cut.

My worry is that this is a zero-sum game and when Gemini catches up on coding, it'll regress to the mean in other areas.

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