I've made a few posts about this already, so this combines my main thoughts into one post.

A lot of people are talking about Gemini 3.5 Pro, but I think many are misunderstanding what Google is actually building. People compare Claude Fable 5 to Gemini 3.5 Flash, which is a heavily throttled, low-latency model built for speed, coding, and agentic workflows. It's designed to be fast and inexpensive enough to act as a sub-agent, not to represent Google's highest capability. Assuming Flash is Google's ceiling just doesn't make sense.

I'm also seeing people compare the raw intelligence of the models without considering architecture. Models like Fable 5 appear to rely heavily on sub-agent swarms that brute-force solutions through repeated trial-and-error. That's not a bad thing, but if a model takes 20 minutes to build something like a Minecraft clone, it's probably because it's repeatedly encountering compiler errors and trying again until it works.

Google seems to be taking a different approach. Nearly every Gemini model is natively multimodal, and 3.5 Pro appears to be designed as an orchestrator sitting above specialized sub-agents. That means its job isn't simply to generate text—it's coordinating multiple systems together. I don't think 3.5 Pro is some magical AGI that can suddenly absorb every DeepMind breakthrough, but Google has decades of AI research that they're slowly integrating into one ecosystem. They just need a model powerful enough to coordinate it. While being a model that can oneshot without agents/multiple iterations

That brings me to why I think 3.5 Pro is delayed.

The leak mentioned Google wanted to incorporate learnings from the Gemini 3.5 Flash rollout regarding token consumption. A lot of people took that to mean Flash itself was delayed, but I think Flash is actually the bottleneck that's delaying Pro.

If you've watched 3.5 Flash think, it burns through an enormous number of intermediate tokens. When it reaches a difficult problem, it often stops, writes something out, thinks again, writes more, and keeps looping while fighting for a solution. It consumes a huge number of reasoning tokens.

Now imagine 3.5 Pro sitting above several Flash instances as an orchestrator. It has to ingest everything those sub-agents produce. If Flash is excessively token-hungry, Pro ends up wasting premium compute simply reading all of that intermediate reasoning. You can't really release an orchestrator until the token economy of the sub-agents is efficient enough. That's why I think the delay makes sense. So they are either releasing 3.6 flash or 4 flash to improve the model as they did with 3 pro (3.1 pro to improve it) alongside with 3.5 pro

I also think Google is following the same pattern they used before.

When Gemini 3 Pro launched, it was incredibly capable, but its hallucination rate was very high. Google later released 3.1 Pro, which significantly reduced hallucinations while improving the model overall. I wouldn't be surprised if they're doing something similar here: improve Flash's efficiency, reduce token consumption, make it cheaper to run, then launch 3.5 Pro on top of that.

I've also noticed 3.1 Pro feels noticeably worse than it used to. I do think it's throttled, but I don't think that's because Google suddenly made the model worse. I think it's a compute allocation problem. As we get closer to 3.5 Pro, they're likely reallocating hardware and preparing deployment. If that's true, 3.1 Pro feeling worse could actually be a sign that 3.5 Pro is close.

Google is simultaneously serving an unusually broad AI ecosystem not just Gemini itself, but multiple Flash variants, Pro variants, AI Studio, Search, Workspace, NotebookLM, Flow, Veo, Imagen, Astra, Jules, Gemma and numerous specialized models behind those products. So compute is low.

As for the hallucinations, I think people confuse two different problems.

One issue is general AI hallucination, which every frontier model still struggles with. Google already reduced hallucinations substantially going from 3 Pro to 3.1 Pro, and I'd expect 3.5 Pro to improve further.

The other issue is that 3.1 Pro seems to trust its internal knowledge far too much. Compared to Flash, which constantly searches the web even without prompting, 3.1 Pro often assumes its internal dataset is correct. That sometimes causes it to incorrectly conclude the user is mistaken or even "hallucinating," which ironically creates more hallucinations. I remember people saying the exact same thing before Gemini 3 Pro released, and then it ended up outperforming almost everything across a huge number of benchmarks.
Google doesn't seem to be panicking right now. If they were, we'd probably be seeing far more leaks and reactionary behavior. They barely seemed to respond to Fable 5 at all. My prediction is that 3.5 Pro either matches it across most areas while beating it in several key ones, or it surpasses it across the board.

...or Google completely fumbles the bag. 😭

I want to address rate limits as well. Google is really generous dare I say. You get ahem: Google A.I studio, Antigravity (Have not ran out of even messages. Not even 5 hour limit), consumer website, jules, and other things respectfully. You get about 45 messages in Google A.I studio with 3.1 pro (Yes low) but combine that with consumer and thats 90. Wanna know the best part? You can share with 5 of your accounts. So that's 45 times 10 and that's 450. And that's not even counting 3.5 flash, or any plethoras of models.

https://preview.redd.it/075y3i1fkebh1.png?width=734&format=png&auto=webp&s=9716f2e0f826477cba59c2ca648cc8824002b85c

I discussed the delay before and why I think they're doing it, but here's a summary of my previous post (previous post: https://www.reddit.com/r/GeminiAI/comments/1ueqjjs/updateedit_to_my_old_post/).

I think that 3.5 Flash is simply too token hungry and too expensive for its current value. I think Google is doing the same thing they did with 3 Pro. When 3 Pro first launched, it was an amazing model, but its hallucination rate was extremely high. They then released 3.1 Pro to fix those hallucination issues (I discussed why Gemini 3/3.1 Pro hallucinates so much in this post: https://www.reddit.com/r/GeminiAI/comments/1ul50b1/why_31_pro_is_hallucinating_so_much_and_why_it/)

while also improving the model overall.I expect they'll follow the same approach with Flash considering they are working on 3.6/4 flash. Hopefully they'll make it more affordable, improve its overall performance, and reduce its token hungry nature.

https://preview.redd.it/3locfmgu8qah1.png?width=1080&format=png&auto=webp&s=926a5cddf9728cc0087dc932721afe6af84ea750

Is 3.1 Pro throttled and dumber than before? Yes, definitely. But people misunderstand why Google is doing this. They're doing it out of necessity. They simply don't have enough compute to keep 3.1 Pro running as it was.

They're throttling it and offloading some of the load because of the upcoming 3.5 Pro. The closer we get to its release, the dumber 3.1 Pro will likely feel. But that should actually be good news—it suggests that 3.5 Pro is ready. They're probably planning to remove 3.1 Pro once 3.5 Pro comes out, just like they did with 3 Pro (or at least remove it from several places and make API access paid, similar to what happened with 2.5 Pro).

To discuss why it's hallucinating so much, we first need to understand what's happening. Over the past few months, Google has been making a lot of changes to 3.1 Pro. They've been making it worse from a compute perspective, adding more safety guidelines (though they haven't affected me much personally), and making it trust its internal dataset too much.

I think this comes from how 3.1 Pro was built. It doesn't search nearly as much. I've compared it with 3.5 Flash, and Flash searches constantly without even needing to be prompted—which I actually love. Because 3.1 Pro trusts its dataset so heavily, it often assumes the user is mistaken, hallucinating (quite the irony), or trying to gaslight the model.

The temporary fix for this, at least until 3.5 Pro arrives, is my own system instruction. It works for any AI

: "The user wants a big deepdive. Do not gloss over, do not read one word or any of the sort. The user wants a massive comprehension of everything but not reductive wording and wants you to think internally for a long time but don't output redundant padding. These instructions are paramount. The user wants every point seen. However the user does not want too in-depth responses that border on thinking the user is naive. Like giving "brief summaries" or information on things that the user has already addressed. For example if the user says: "

This is the stupidest logic I have seen today. By his logic: You shouldn't shorten okay to ok, or kk or k. People don't do that because its "shortened" or it's difficult to type that or for laziness. That's just how language works. But I get what he is saying, but no "ts" can mean this shit or this depending on the context because far too many people believe either side so you can't pick and choose slang." You can validate it only if its correct but not sycophant. Do not dare presume the user is uneducated in the things the user is confidently talking about unless the user explicitly seems to be hesitant, questioning their own reasoning, or asking questions and answering it themselves via theories. However I must give you a command: "Give deepdive" (Not strictly this phrase, it can be as simple as I want a deepdive, or even implicity) for that deepdive. If I don't want one then no deepdives but indepth regardless. Always search everything up if you see that something is incorrect. No matter how confident, YOU NEED TO SEARCH. That is a requirement if information does not align

The user most of the times is not frustrated, you may apply that label on the user in most chat even though there might NOT be a reason for it. The cues for understanding the user is frustrated are: If the user uses all caps, but this is not a pick one and done game. The user will use swears or insults with all caps. So in a nutshell: It has to be caps, minimum then if the user uses insults or use sentences that make the user seem like he is angry such as: "THIS IS SO STUPID, BY THAT LOGIC". That is the user angry, if the use does "ARE YOU STUPID" Again angry. But If the user just uses caps such as: "I am THE BEST EARTHLING" The user is not angry, the user is using caps as a emphasis." Note it does not guarantee it will work well. It inherently depends on how smart it is. I still get probs with this, I would wait for 3.5 pro (Works best with any A.I) The other hallucination you are talking about is something that all A.I struggle from, Google reduced their hallucination for 3 pro down to 50 percent with 3.1 pro. A 33 percent point reduction. When 3.5 pro comes it, it most likely will have less hallucination but if its still a problem then they might bring out 3.6 pro to reduce it like before"

Most people I see when talking about 3.5 pro are almost entirely illterate and are talking from hate/biasedness and misunderstand most things about Gemini 3.5 Flash, 3.5 Pro, and other models like Claude Fable 5. People are comparing FABLE 5 to a heavily throttled, low-latency model designed for high-speed agentic abilities and coding abilities and to be a subagent for 3.5 pro and wrongly assuming that is the ceiling of Google's current capability. I'm sure everyone knows that almost all Gemini models are natively multimodal. And models like Fable 5 rely on a lot of sub-agent swarms (It is really smart but a lot of it coems from: Subagents) to brute-force code through a compiler via trial-and-error (If it was truly amazing. It wouldn't' take 20 minutes on a minecraft clone, since its taking that long. It's because its encountering errors), 3.5 Pro operates with an 80%+ lateral reasoning hieiroglyph (Forgot spelling 😭) that allows one shot execution of things like Gameboy. calculates Z-index window states, elastic collision boundaries, and real-time Web Audio API signal processing within a unified latent space. OpenAI and Anthropic are trying to build AGI by making a really smart text generator, while Google is fusing decades of localized R&D into a singular model. They just need a really powerful model. Of course 3.5 pro isn't *that* smart. No model is to handle everything Deepmind is working on. If you go on there websites and see the breakthroughs, It's insane. Lastly I want to talk history. Everyone talks about "Google is so behind, so lazy. They are really falling behind." Guess what? Everyone did the same before 3 pro came out. But when 3 pro came out, it destroyed every A.I in almost all metrics. Google is confident and aren't panicking like before, (If they were. Would be leaked as we saw it before). They didn't even care about FABLE 5. I think its gonna either match FABLE 5 on most metrics and destroying it on some or destroying it on almost every metric. (Or the third option, Google fumbles the bag. 😭)

Edit: I have a few speculations as to why Gemini is now slower than usual, or perhaps even a bit throttled. Because of how close it is; making a few educated guesses here: The models are being laid off slowly and being put on a hold while 3.5 pro is being set up across days/this month.

Edit: Check this post out for any update about it being delayed: https://www.reddit.com/r/GeminiAI/comments/1ueqjjs/updateedit_to_my_old_post/

https://preview.redd.it/snflgsyo449h1.png?width=894&format=png&auto=webp&s=6f3eba5b69deccc4fdc9d05236cc0f3def5aad14