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Improved Gemini 2.5 Flash and Flash-Lite

developers.googleblog.com

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Re: Improved Gemini 2.5 Flash and Flash-Lite

#41

Non-AI Summary: Both models have improved intelligence on Artificial Analysis index with lower end-to-end response time. Also 24% to 50% improved output token efficiency (resulting in lower cost). Gemini 2.5 Flash-Lite improvements include better instruction following, reduced verbosity, stronger multimodal & translation capabilities. Gemini 2.5 Flash improvements include better agentic tool use and more token-effici…

I think “Non-AI summary” is going to become a thing. I already enjoyed reading it more because I knew someone had thought about the content.

Re: Improved Gemini 2.5 Flash and Flash-Lite

#42

Google seems to be the main foundation model provider that's really focusing on the latency/TPS/cost dimensions. Anthropic/OpenAI are really making strides in model intelligence, but underneath some critical threshold of performance, the really long thinking times make workflows feel a lot worse in collaboration-style tools, vs a much snappier but slightly less intelligent model. It's a delicate balance, because thes…

Can't agree with that. Gemini doesn't lead just on price/performance - ironically it's the best "normie" model most of the time, despite it's lack of popularity with them until very recent.

It's bad at agentic stuff, especially coding. Incomparably so compared to Claude and now GPT-5. But if it's just about asking it random stuff, and especially going on for very long in the same conversation - which non-tech users have a tendency to do - Gemini wins. It's still the best at long context, noticing things said long ago.

Earlier this week I was doing some debugging. For debugging especially I like to run sonnet/gpt5/2.5-pro in parallel with the same prompt/convo. Gemini was the only one that, 4 or so messages in, pointed out something very relevant in the middle of the logs in the very first message. GPT and Sonnet both failed to notice, leading them to give wrong sample code. I would've wasted more time if I hadn't used Gemini.

It's also still the best at a good number of low-resource languages. It doesn't glaze too much (Sonnet, ChatGPT) without being overly stubborn (raw GPT-5 API). It's by far the best at OCR and image recognition, which a lot of average users use quite a bit.

Google's ridiculously bad at marketing and AI UX, but they'll get there. They're already much more than just a "bang for the buck" player.

FWIW I use all 3 above mentioned on a daily basis for a wide variety of tasks, often side-by-side in parallel to compare performance.

Re: Improved Gemini 2.5 Flash and Flash-Lite

#43

Okay this is a nitpick but why wouldn't you increment a part of the version number to signify that there is an improvement? These releases are confusing.

I would assume that it will supersede the model that they currently have. So eventually 2.5 flash will be the new and improved 2.5 Flash rather than 2.6.

Same way that openai updated their 4-o models and the like, which didn't turn out so well when it started glazing everyone and they had to revert it (maybe that was just chat and not api)

Re: Improved Gemini 2.5 Flash and Flash-Lite

#44

Okay this is a nitpick but why wouldn't you increment a part of the version number to signify that there is an improvement? These releases are confusing.

This is also my beef...

Anthropic kind of did the same thing [1] except it back-fired recently with the cries of "nerfing".

We buy these tokens, which are very hard to do in limited tiers, they expire after only a year, and we don't even know how often the responses are changing in the background. Even a 1% improvement or reduction I would want disclosed.

Really scary foundation AI companies are building on IMO. Transparency and access is important.

[1] https://status.claude.com/incidents/h26lykctfnsz

Re: Improved Gemini 2.5 Flash and Flash-Lite

#45
post #42

Google seems to be the main foundation model provider that's really focusing on the latency/TPS/cost dimensions. Anthropic/OpenAI are really making strides in model intelligence, but underneath some critical threshold of performance, the really long thinking times make workflows feel a lot worse in collaboration-style tools, vs a much snappier but slightly less intelligent model. It's a delicate balance, because thes…

Can't agree with that. Gemini doesn't lead just on price/performance - ironically it's the best "normie" model most of the time, despite it's lack of popularity with them until very recent. It's bad at agentic stuff, especially coding. Incomparably so compared to Claude and now GPT-5. But if it's just about asking it random stuff, and especially going on for very long in the same conversation - which non-tech users h…

Does it still try to 'unplug' itself if it gets something wrong, or did they RL that out yet?

Re: Improved Gemini 2.5 Flash and Flash-Lite

#46
post #5

Gemini 2.5 Flash is an impressive model for its price. However, I don't understand why Gemini 2.0 Flash is still popular. From OpenRouter last week: * xAI: Grok Code Fast 1: 1.15T * Anthropic: Claude Sonnet 4: 586B * Google: Gemini 2.5 Flash: 325B * Sonoma Sky Alpha: 227B * Google: Gemini 2.0 Flash: 187B * DeepSeek: DeepSeek V3.1 (free): 180B * xAI: Grok 4 Fast (free): 158B * OpenAI: GPT-4.1 Mini: 157B * DeepSeek: De…

My one big problem with OpenRouter is that, as far as I can tell, they don't provide any indication of how many companies are using each model.

For all I know there are a couple of enormous whales on there who, should they decide to switch from one model to another, will instantly impact those overall ratings.

I'd love to have a bit more transparency about volume so I can tell if that's what is happening or not.

Re: Improved Gemini 2.5 Flash and Flash-Lite

#47
post #19

LLM Model versioning really makes me perplex those days...

Yeah, why is it that working with AI makes people completely forget what version numbers mean?

gemini-2.5-flash-preview-09-2025 - what are they thinking?

I thought about joking that they had AI name it for them, but when I asked Gemini, it said that this name was confusing, redundant, and leads to unnecessarily high cognitive load.

Maybe Googlers should learn from their own models.

Re: Improved Gemini 2.5 Flash and Flash-Lite

#48

Google seems to be the main foundation model provider that's really focusing on the latency/TPS/cost dimensions. Anthropic/OpenAI are really making strides in model intelligence, but underneath some critical threshold of performance, the really long thinking times make workflows feel a lot worse in collaboration-style tools, vs a much snappier but slightly less intelligent model. It's a delicate balance, because thes…

IMO the race for Latency/TPS/cost is entirely between grok and gemini flash. No model can touch them (especially for image to text related tasks), openai/anthropic seem entirely uninterested in competing for this.

Re: Improved Gemini 2.5 Flash and Flash-Lite

#49
post #5

Gemini 2.5 Flash is an impressive model for its price. However, I don't understand why Gemini 2.0 Flash is still popular. From OpenRouter last week: * xAI: Grok Code Fast 1: 1.15T * Anthropic: Claude Sonnet 4: 586B * Google: Gemini 2.5 Flash: 325B * Sonoma Sky Alpha: 227B * Google: Gemini 2.0 Flash: 187B * DeepSeek: DeepSeek V3.1 (free): 180B * xAI: Grok 4 Fast (free): 158B * OpenAI: GPT-4.1 Mini: 157B * DeepSeek: De…

Price, 2.0 Flash is cheaper than 2.5 Flash but still very good model.

API usage of Flash 2.0 is free, at least till you hit a very generous bound. It's not simply a trial period. You don't even need to register any payment details to get an API key. This might be a reason for its popularity. AFAIK only some Mistral offerings have a similar free tier?

Re: Improved Gemini 2.5 Flash and Flash-Lite

#50

Google seems to be the main foundation model provider that's really focusing on the latency/TPS/cost dimensions. Anthropic/OpenAI are really making strides in model intelligence, but underneath some critical threshold of performance, the really long thinking times make workflows feel a lot worse in collaboration-style tools, vs a much snappier but slightly less intelligent model. It's a delicate balance, because thes…

I would be surprised if this dichotomy you're painting holds up to scrutiny.

My understanding is Gemini is not far behind on "intelligence", certainly not in a way that leaves obvious doubt over where they will be over the next iteration/model cycles, where I would expect them to at least continue closing the gap. I'd be curious if you have some benchmarks to share that suggest otherwise.

Meanwhile, afaik something Google has done, and perhaps relates back to your point re "latency/TPS/cost dimensions" that other providers aren't doing as much is integrating their model into interesting products beyond chat, at a pace that seems surprising given how much criticism they had been taking for being "slow" to react to the LLM trend.

Besides the Google Workspace surface and Google search, which now seem obvious - there are other interesting places where Gemini will surface - https://jules.google/ for one, to say nothing of their experiments/betas in the creative space - https://labs.google/flow/about

Another I noticed today: https://www.google.com/finance/beta

I would have thought putting Gemini on a finance dashboard like this would be inviting all sorts of regulatory (and other) scrutiny... and wouldn't be in keeping with a "slow" incumbent. But given the current climate, it seems Google is plowing ahead just as much as anyone else - with a lot more resources and surface to bring to bear. Imagine Gemini integration on Youtube. At this point it just seems like counting down the days...

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