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Gemini 3.7 Flash

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321–330 of 525 posts

Re: Gemini 3.7 Flash

#321

The Gemini Flash models makes perfect sense to me coming from a company like Google. Google AI Mode for search is a product I really find useful. It makes sense that Google focused on smaller, faster yet smart enough models that wouldn't break your bank on inference. It plays well into their product ecosystem. Google AI Mode consistently gets me consistently good results and good speeds. It really changes what "googl…

I similarly have a weird affinity for Gemini that I can't really articulate. I used Gemini's free chat and found it great for exploring technical topics (and random one-off general walking-around-questions) and appreciated its speed, tone and accuracy. I spent a month playing with Gemini CLI / Antigravity and found it also an effective coding agent, at least for my workflow (entirely in the loop development and review). I also was really surprised that I could just paste it images of a project I was working on and have it immediately understand what it was looking at -- which I've come to learn is considered a unique strong point for Gemini. I've been playing with GPT5.6 for about a month and it's definitely powerful but I honestly think I'll go back to Gemini. There's something kind of charming about working with an AI that not only is particularly good at web search and information gathering, but also one that doesn't feel like some superhuman overengineering freak when it comes to code.

Re: Gemini 3.7 Flash

#322
post #41

They 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 com…

Why is Gemini represented by points on this cost-quality plane, while competitor's models are represented by curves?

For what it's worth the source of the data[0] does have 3.7 flash with all 3 reasoning levels. 3.5/3.6 are in fact just the single points though (high reasoning). The datapoint in the announcement screenshot is either med or high, but they're pretty much exactly the same so can't say for certain.

[0]: https://deepswe.datacurve.ai/

Re: Gemini 3.7 Flash

#323
post #41

They 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 com…

Why is Gemini represented by points on this cost-quality plane, while competitor's models are represented by curves?

That graph has to be made because an Exec didn't like that graph went down to the right instead of up and to the right. How do you make a graph with 0 on the far right and counts up by going left of 0? What number line is that?

Re: Gemini 3.7 Flash

#324
post #86

Earlier quoted context omitted.

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.

On DeepSwe it's strictly beaten by Luna on max, cost and result. Damn, Luna on max is as good on DeepSWE as Kimi k3, I think I dismissed this model unjustly.

This is why benchmarks are scary, since Artificial Analysis puts it a fair bit behind Kimi K3.

Kimi K3 is a beast though, just costly.

Re: Gemini 3.7 Flash

#325
post #60

Earlier quoted context omitted.

I've blown away by flash 3.6's speed while Opus chugs along for _hours_ on similar tasks. I've gotten into a opus designed -> gemini implemented -> opus reviewed dev cycle recently.

> I've gotten into a opus designed -> gemini implemented -> opus reviewed dev cycle recently. This is what I do too.

Last time I tried it, Flash introduced too many errors due to sloppiness. Is it more reliable at following instructions now?

Re: Gemini 3.7 Flash

#326
post #106

Here's a image->html test. Gemini has always swung above its weight class for vision work, so I'm always eager to try it with this. Original images: https://image.non.io/neonRamenDesigns.webp Gemini 3.7 build: https://html.non.io/neonRamenGemini3.7 Opus 5 build for comparison: https://html.non.io/neonRamen Opus is still best in class for this, but it's worth noting how well Gemini 3.7 does vs a more comparable LLM pr…

There is some irony being a developer and reading along the lines of: "oh look at the comparison between these models executing a task for a few cents on a job i'd be charging 1k minimum"

I know what you're saying but this is the most tedious, soul crushing dev work there is

Re: Gemini 3.7 Flash

#327

I don't get it, Google could heavily subsidy their Gemini models to make it more attractive, but they prefer to not do it. I don't know one soul who is using Gemini models to code. Even OpenAI who doesn't have money or capacity is offering their Luna model at $1.2 per 1M/out.

Google was cash-flow negative in Q2 2026, and is raising a lot of debt.

I am not sure they can afford to subsidize Gemini more than they already do.

Re: Gemini 3.7 Flash

#329
post #240

Earlier quoted context omitted.

Also best at OpenSCAD, seemingly for the same reason, at least in terms of "iterate on a design, comparing visual output to target".

Are you manually rendering previews of its OpenSCAD output to create images for it to review, or do you have a workflow that automates that?

Personally both, i use openscad with opencode, and paste images but it is pretty often the modell decides by itself it wants to see a render and uses the render shell commands to get a image to look at.

Re: Gemini 3.7 Flash

#330
post #240
post #70

Earlier quoted context omitted.

gemini flash is probably the best model for visual tasks right now. they also make it really easy to ingest videos

Also best at OpenSCAD, seemingly for the same reason, at least in terms of "iterate on a design, comparing visual output to target".

+1 gemini models where really the only ones fullt grasping spatial reasoning even compared to opus (at least when i last cared to check it)
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