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Gemini 2.5 Flash

developers.googleblog.com

261–270 of 582 posts

Re: Gemini 2.5 Flash

#261
post #207

Earlier quoted context omitted.

Google has killed so many amazing businesses -- entire industries, even, by giving people something expensive for free until the competition dies, and then they enshittify hard. It's cool to have access to it, but please be careful not to mistake corporate loss leaders for authentic products.

In this case, Google is a large investor in Anthropic. I agree that giving away access to expensive models long term is not a good idea on several fronts. Personally, I subscribe to Gemini Advanced and I pay for using the Gemini APIs. EDIT: a very good deal, at $10/month is https://apps.abacus.ai/chatllm/ that gives you access to almost all commercial models as well as the best open weight models. I have never come c…

The problem with tools like this is that somewhere in the chain between you and the LLM are token reducing “features”. Whether it’s the system prompt, a cheaper LLM middleman, or some other cost saving measure.

You’ll never know what that something is. For me, I can’t help but think that I’m getting an inferior service.

Re: Gemini 2.5 Flash

#262
post #192

Earlier quoted context omitted.

After comparing Gemini Pro and Claude Sonnet 3.7 coding answers side by side a few times, I decided to cancel my Anthropic subscription and just stick to Gemini.

Yes, IME, Anthropic seemed to be ahead of Google by a decent amount with Sonnet 3.5 vs 1.5 Pro. However, Sonnet 3.7 seemed like a very small increase, whereas 2.5 Pro seemed like quite a leap. Now, IME, Google seems to be comfortably ahead. 2.5 Pro is a little slow, though. I'm not sure which model Google uses for the AI answers on search, but I find myself using Search for a lot of things I might ask Gemini (via 2.5…

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Re: Gemini 2.5 Flash

#263
post #192

Earlier quoted context omitted.

After comparing Gemini Pro and Claude Sonnet 3.7 coding answers side by side a few times, I decided to cancel my Anthropic subscription and just stick to Gemini.

Yes, IME, Anthropic seemed to be ahead of Google by a decent amount with Sonnet 3.5 vs 1.5 Pro. However, Sonnet 3.7 seemed like a very small increase, whereas 2.5 Pro seemed like quite a leap. Now, IME, Google seems to be comfortably ahead. 2.5 Pro is a little slow, though. I'm not sure which model Google uses for the AI answers on search, but I find myself using Search for a lot of things I might ask Gemini (via 2.5…

How's is the speed of Gemini vs 3.7?

Re: Gemini 2.5 Flash

#264

Earlier quoted context omitted.

Can I ask a serious question. What task are you writing where its ok to get 7% error rate. I can't get my head around how this can be used.

In my case, I have workloads like this where it’s possible to verify the correctness of the result after inference, so any success rate is better than 0 as it’s possible to identify the “good ones”.

Aren’t you basically just saying you are able to measure the error rate? I mean that’s good, but already a given in this scenario where hes reporting the 7% error rate.

Re: Gemini 2.5 Flash

#265
post #6

Gemini flash models have the least hype, but in my experience in production have the best bang for the buck and multimodal tooling. Google is silently winning the AI race.

I remember everyone saying its a two horse race between Google and OpenAI, then DeepSeek happened. Never count out the possibility of a dark horse competitor ripping the sod right out from under

How is deepseak doing though? It seemed like they probably just ingested ChatGPT. https://www.forbes.com/sites/torconstantino/2025/03/03/deeps...

Still impressive but would really put a cap on expectations for them.

Re: Gemini 2.5 Flash

#266

Google making Gemini 2.5 Pro (Experimental) free was a big deal. I haven't tried the more expensive OpenAI models so I can't even compare, only to the free models I have used of theirs in the past. Gemini 2.5 Pro is so much of a step up (IME) that I've become sold on Google's models in general. It not only is smarter than me on most of the subjects I engage with it, it also isn't completely obsequious. The model push…

I had a very interesting long debate/discussion with Gemini 2.5 Pro about the Synapse-Evolve bank debacle among other things. It really feels like debating a very knowledgeable and smart human.

Re: Gemini 2.5 Flash

#267
An often overlooked feature of the Gemini models is that they can write and execute Python code directly via their API.

My llm-gemini plugin supports that: https://github.com/simonw/llm-gemini

  uv tool install llm
  llm install llm-gemini
  llm keys set gemini
  # paste key here
  llm -m gemini-2.5-flash-preview-04-17 \
    -o code_excution 1 \
    'render a mandelbrot fractal in ascii art'
I ran that just now and got this: https://gist.github.com/simonw/cb431005c0e0535343d6977a7c470...

They don't charge anything extra for code execution, you just pay for input and output tokens. The above example used 10 input, 1,531 output which is $0.15/million for input and $3.50/million output for Gemini 2.5 Flash with thinking enabled, so 0.536 cents (just over half a cent) for this prompt.

Re: Gemini 2.5 Flash

#268
post #59

For a non programmer like me google is becoming shockingly good. It is giving working code the first time. I was playing around with it asked it to write code to scrape some data of a website to analyse. I was expecting it to write something that would scrape the data and later I would upload the data to it to analyse. But it actually wrote code that scraped and analysed the data. It was basic categorizing and counti…

That's the opposite experience of my wife who's in tech but also a non programmer. She wanted to ask Gemini to write code to do some basic data analysis things in a more automated way than Excel. More than once, Gemini wrote a long bash script where some sed invocations are just plain wrong. More than once I've had to debug Gemini-written bash scripts. As a programmer I knew how bash scripts aren't great for readabil…

The AIs like many things out there work like an "evil genie". They'll give you what you asked for. The problem is typically that users ask for the wrong thing.

I've noticed beginners make mistakes like using singular terms when they should have used plural ("find the bug" vs "find the bugs"), or they fail to specify their preferred platform, language, or approach.

You mentioned your wife is using Excel, which is primarily used on Windows desktops and/or with the Microsoft ecosystem of products such as Power BI, PowerShell, Azure, SQL Server, etc...

Yet you mention she got a bash script using sed, both of which are from the Linux / GNU ecosystem. That implies that your wife didn't specify that she wanted a Microsoft-centric solution to her problem!

The correct answer here would have likely to have been to use Microsoft Fabric, which is an entire bag of data analysis and reporting tools that has data pipelines, automation, publishing, etc...

Or... just use the MashUp engine that's built-in to both Excel and PowerBI, which allows a surprisingly complex set of text, semi-structured, and tabular data processing. It can re-run the import and update graphs and charts with the new data.

PS: This is similar to going up to a Node.js programmer with a request. It doesn't matter what it is, they will recommend writing JavaScript to solve the problem. Similarly, a C++ developer will reach for C++ to solve everything they're asked to do. Right now, the AIs strongly prefer Linux, JavaScript, and especially Python for problem solving, because that's the bulk of the open-source code they were trained with.

Re: Gemini 2.5 Flash

#270

Earlier quoted context omitted.

Could you please expand, on both your points?

It is more gut feel than a rational or carefully reasoned argument. I think Pichai has been an exceptional revenue maximizer but he lacks vision. I think he is probably capable of squeezing tremendous revenue out of AI once it has been achieved. I like Hassabis in a "good vibe" way when I hear him speak. He reminds me of engineers that I have worked with personally and have gained my respect. He feels less like a pro…

> Altman made a decision to pivot the company towards product which led to the exodus of early research talent.

Who was going to fund the research though?

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