Gemini 3.5 Flash

f311a

$9/1M output

alexdns

Its Gemini 3.5 Flash

swe_dima

Flash family but costs like a Pro. $9 vs $12 for output.

asar

$1.5/m input tokens $9/m output tokens 6x the price of 3.1 flash lite

himata4113

Engineers at google have publically stated that the models are too big and are far from their potencial. Glad they're being proven right with every release. They continue to focus on smaller models while openai and anthropic are increasing compute requirements for their SOTA models.

golfer

Here's the benchmark scoreboard they published: https://storage.googleapis.com/gweb-uniblog-publish-prod/ori...

mixtureoftakes

benchmarks look REALLY good, the price hike is big but it also beats sonnet 4.6 in every discipline?

SXX

> Create animated SVG of a frog on a boat rowing through jungle river. Single page self contained HTML page with SVG 3.5 Flash: Thinking Medium - 7516 tokens https://gistpreview.github.io/?5c9858fd2057e678b55d563d9bff0... 3.5 Flash: Thinking High - 7280 tokens https://gistpreview.github.io/?1cab3d70064349d08cf5952cdc165... 3.1 Pro - 28,258 tokens https://gistpreview.github.io/?6bf3da2f80487608b9525bce53018... Though 3.1 took 3 minutes of thinking to generate, but it only one that got animated movement.

cesarvarela

Add Flash to the title, please.

benbencodes

Pricing is now live on ai.google.dev/pricing: Gemini 3.5 Flash: $0.75 input / $4.50 output per 1M tokens, 1M context window. The output price explicitly "includes thinking tokens" — which is why it's higher than a typical flash-class model. For comparison within the Gemini lineup: - Gemini 2.5 Flash: $0.30 / $2.50 - Gemini 3.1 Flash-Lite: $0.25 / $1.50 - Gemini 3.1 Pro Preview: $2.00 / $12.00 So 3.5 Flash is ~2.5x more expensive input vs 2.5 Flash. The pricing and "including thinking tokens" framing position it as a reasoning-capable flash model rather than just a pure speed optimization.

aliljet

Is there a good benchmark tracking hallucinations? The models are all incredibly good now, even the open ones, and my hope is that the rate of hallucinations is something that's falling off in concert with larger and larger context lengths.

bakugo

Triple the price of the last Flash model ($3 -> $9 per 1M output). Quickly approaching Sonnet prices. Feels like the AI pricing noose is tightening sooner rather than later.

eis

3.5 Flash was more expensive than 3.1 Pro to run the Artifical Analysis test suite. $1551 for 3.5 Flash [0] vs $892 for 3.1 Pro [1]. That's 74% more cost while ranking lower. It's 2.5x as fast but I don't think the bang for the buck is there anymore like it was with 3.0 Flash. I'm a bit bummed out to be honest. I did not expect such a huge (3x) price increase from 3.0 Flash and I bet many people will not just blindly upgrade as the value proposition is widely different. One interesting point to note is that Google marked the model as Stable in contrast to nearly everything else being perpetually set as Preview. [0] https://artificialanalysis.ai/models/gemini-3-5-flash [1] https://artificialanalysis.ai/models/gemini-3-1-pro-preview

nightski

AI being a product is not the future. It's more like an operating system that deserves to be open and free (aka Linux). Unless that happens we are in for a very dystopian future. I wish I had the intelligence, resources and/or connections to try and make that happen.

HardCodedBias

Oh boy. GDM is making (or has been backed into a corner into making) the bet that high throughput, low latency, low capability models are the path forward. That probably works for vibe coded apps by non-practitioners. I suspect that practitioners/professionals will wait longer for better results.

OsrsNeedsf2P

Beats 3.1 Pro for price per token, but artificial analysis is showing it's dumber per token and costs more overall

s3p

Yikes. I think the concept of a 'flash' model is changing, no? Google used to market this as its lower-intelligence, faster, cheaper option. I appreciate that they are delivering on both of those, but personally I would appreciate if they could create an incremental knowledge improvement while holding price steady. Fortune 500 companies have to make their money I guess.

noelsusman

The Artificial Analysis benchmark results are pretty underwhelming. Roughly the same "intelligence" as MiMo-V2.5-Pro for over 3x the cost. We'll have to see how that translates to actual usage but it's not a great sign.

merb

Stil no new processor version for document ai https://docs.cloud.google.com/document-ai/docs/release-notes that is so weird. (Customer extractor) It’s not possible to uptrain on preview releases and it did not get that much love for a while.

warthog

GPT-5.5 on the benchmarks still seem to perform better than this Plus the vibe of the gemini models are so weird particularly when it comes to tool calling At this point I kinda need them to shock me to make the switch