Developer Blog: https://blog.google/technology/developers/build-with-gemini-...

Model Card [pdf]: https://deepmind.google/models/model-cards/gemini-3-flash/

Gemini 3 Flash in Search AI mode: https://blog.google/products/search/google-ai-mode-update-ge...

Also I don't see it written in the blog post but Flash supports more granular settings for reasoning: minimal, low, medium, high (like openai models), while pro is only low and high.

I have been playing with it for the past few weeks, it’s genuinely my new favorite; it’s so fast and it has such a vast world knowledge that it’s more performant than Claude Opus 4.5 or GPT 5.2 extra high, for a fraction (basically order of magnitude less!!) of the inference time and price

Hoping that the local ones keep progressively up (gemma-line)

Is there an OSS model that's better than 2.0 flash with similar pricing, speed and a 1m context window?

Edit: this is not the typical flash model, it's actually an insane value if the benchmarks match real world usage.

> Gemini 3 Flash achieves a score of 78%, outperforming not only the 2.5 series, but also Gemini 3 Pro. It strikes an ideal balance for agentic coding, production-ready systems and responsive interactive applications.

The replacement for old flash models will be probably the 3.0 flash lite then.

1, has anyone actually found 3 Pro better than 2.5 (on non code tasks)? I struggle to find a difference beyond the quicker reasoning time and fewer tokens.

2, has anyone found any non-thinking models better than 2.5 or 3 Pro? So far I find the thinking ones significantly ahead of non thinking models (of any company for that matter.)

With this release the "good enough" and "cheap enough" intersect so hard that I wonder if this is an existential threat to those other companies.

-> 2.5 Flash Lite is super fast & cheap (~1-1.5s inference), but poor quality responses.

-> 2.5 Flash gives high quality responses, but fairly expensive & slow (5-7s inference)

I really just need an in-between for Flash and Flash Lite for cost and performance. Right now, users have to wait up to 7s for a quality response.

Pipe dream right now, but 50 years later? Maybe

Google keeps their models very "fresh" and I tend to get more correct answers when asking about Azure or O365 issues, ironically copilot will talk about now deleted or deprecated features more often.

They are pushing the prices higher with each release though: API pricing is up to $0.5/M for input and $3/M for output

For comparison:

Gemini 3.0 Flash: $0.50/M for input and $3.00/M for output

Gemini 2.5 Flash: $0.30/M for input and $2.50/M for output

Gemini 2.0 Flash: $0.15/M for input and $0.60/M for output

Gemini 1.5 Flash: $0.075/M for input and $0.30/M for output (after price drop)

Gemini 3.0 Pro: $2.00/M for input and $12/M for output

Gemini 2.5 Pro: $1.25/M for input and $10/M for output

Gemini 1.5 Pro: $1.25/M for input and $5/M for output

I think image input pricing went up even more.

Correction: It is a preview model...

For comparison, from 2.5 Pro ($1.25 / $10) to 3 Pro ($2 / $12), there was 60% increase in input tokens and 20% increase in output tokens pricing.

Just avoiding/fixing that would probably speed up a good chunk of my own queries.

I'm more excited to see 3 Flash Lite. Gemini 2.5 Flash Lite needs a lot more steering than regular 2.5 Flash, but it is a very capable model and combined with the 50% batch mode discount it is CHEAP ($0.05/$0.20).

I'm speculating but Google might have figured out some training magic trick to balance out the information storage in model capacity. That or this flash model has huge number of parameters or something.

Turns out Gemini 3 Flash is pretty close. The Gemini CLI is not as good but the model more than makes up for it.

The weird part is Gemini 3 Pro is nowhere as good an experience. Maybe because its just so slow.

Skatval is a small local area I live in, so I know when it's bullshitting. Usually, I get a long-winded answer that is PURE Barnum-statement, like "Skatval is a rural area known for its beautiful fields and mountains" and bla bla bla.

Even with minimal thinking (it seems to do none), it gives an extremely good answer. I am really happy about this.

I also noticed it had VERY good scores on tool-use, terminal, and agentic stuff. If that is TRUE, it might be awesome for coding.

I'm tentatively optimistic about this.

It's 1/4 the price of Gemini 3 Pro ≤200k and 1/8 the price of Gemini 3 Pro >200k - notable that the new Flash model doesn’t have a price increase after that 200,000 token point.

It’s also twice the price of GPT-5 Mini for input, half the price of Claude 4.5 Haiku.

Flash is meant to be a model for lower cost, latency-sensitive tasks. Long thinking times will both make TTFT >> 10s (often unacceptable) and also won't really be that cheap?

I assume that these are just different reasoning levels for Gemini 3, but I can't even find mention of there being 2 versions anywhere, and the API doesn't even mention the Thinking-Pro dichotomy.