I'm on the Student AI Pro tier with 5TB of storage and decided to try Gemini 4 Argon in the web client.

So far, I actually prefer it to GPT-6 Sol High for finding and analyzing information. It surfaced more relevant sources, inferred what I was trying to accomplish better, and gave me more useful answers for practical real-world questions, whereas GPT often leans toward more theoretical responses.

The downside is that I burned through the usage allowance incredibly quickly.

I only had four chats with around 2–3 messages each using Medium reasoning, and that was enough to exhaust my hourly allowance and use about 5% of the weekly one. Now I've been dropped down to 3.5 Flash-Lite.

For comparison, I've never managed to hit the usage limits on OpenAI, even though I use High reasoning for basically everything.

Really disappointing, because I was otherwise very impressed with Argon.

(post is GPT 6 reworded because of the stupid filter on this sub)

EDIT:

Questions asked:

1. Analysis on a macro-economic theory
2. Compare two USB-C AMP/DAC dongles
3. Compare Jetbrains AI tools
4. Upgrade the custom ROM of an old phone

I'm too raged to even articulate this properly, but seeing this really put things into perspective.

OpenCode can offer this level of access through API billing, but Google can't even give Pro subscribers minimal usage?

Instead, the pitch is essentially: "Hey, Pro subscribers get Gemini 4 Argon... Web only"

A couple weeks ago Claude Opus 5.5 made a 14s product film for my bookkeeping app in React + Remotion from one long brief: real UI from the repo, real design tokens, no After Effects. When Argon came out yesterday I gave it the exact same brief on the same repo.

What I noticed: Argon rebuilt noticeably more of the real UI and packs more information into each frame. Opus made fewer, bigger camera moves and holds shots longer, so it feels more like a film than a walkthrough. I lean Opus, but Argon's UI fidelity is genuinely better, and I'm curious what people here think. On the other hand Aragon did some weird linings in the logo.

I'm on the ultra plan and have been using argon for all sorts of things, like designing and critiquing recipes/weighing different cooking techniques against each other (I have a custom DB based on "The Flavor Bible" which it consults for ingredient pairings and several custom skills), creating custom 3D-printable models in Fusion 360, creative writing, auditing and improving my massive homelab and various custom apps and infrastructure, explaining complex scientific topics, helping me rehab my shoulder and knees, etc. and it has been the best model for all of these tasks out of all the models I've tried (and I've tried basically all of them).

I don't really know if it's the best for coding, or for generating SVGs of pelicans, or doing homework, or whether or not it knows if I should drive or walk to the car wash. I don't use it for anything like that and I don't really see the point. But for general knowledge, spatial reasoning, and just apparent intelligence, it seems to be knocking it out of the park with what I use it for.

Yeah, usage goes fast, but honestly I've gotten things done in these last two days which I've previously just straight-up given up on with other models due to not getting the output that I want. To me that's worth it. Time is money as they say.

Anyone else having similar experiences? Unique use cases where it seems to be doing particularly well?

Excited to see what the pro/flash versions are like.

Year ago I could chat with gemini for 2 hour straight and maybe 10% of limit was used, and now i tried the argon. Asked for any information about the strategy of pro plan being for 3 bucks a month on discount and next tier being 100, and got biggest bullshit ever, started talking about a 3.5 PRO, alr I asked a followup question about his 3.5 pro rolling out. Told me that 3.5 is being in "cooming soon phase" but it is internally still hosted by google on their tpu. Then i looked at my limits and 30% are gone. 2 QUESTIONS AND 30% GOOGLE??

Looks like we have confirmation. Argon is not a Pro model as it is listed separate from Pro. Not only that, Argon is listed as being a higher tier above Pro. Is 4.0 Pro going to be released then?

https://support.google.com/gemini/answer/18648722?hl=en&ref_topic=13194540

I tested out Argon on my sibling's AI Pro account and OMG the usage limits are horrendous. Simply asking "Compare haiku 5.5 with 3.8 flash" used up 8% of her quota. How am I getting more usage out of Opus 5.5 on Claude Pro when it's 2x more expensive? And once the 50% discount ends on Nov 30, these limits are going straight down the drain.

I only loved 3.7 Flash because of the blazing speed. 3.8 Flash doenst meaningfully improve for my use case. When DeepSeek v4.1 Flash dropped, I switched over immediately since it's cheaper and faster (but oh boy does it think a lot!).

I just want a Gemini 4 Flash running at 300 tps at Sonnet 5.5 level intelligence with actually usable limits. Argon's quota is an absolute joke.

This isn't exactly a groundbreaking use case but it's something I never imagined I could do.

I've always wanted my Google Pixel to display the day of the week and the month in the status bar. The existing apps that do this on the Play Store never looked native on a Pixel device, or were buggy/poorly rated.

Now that Argon released, I decided to give it a try.

I have zero coding or development experience and was able to get this running on my pixel in about 3-4 hours (most of which was learning how to even install and use Antigravity).

I'm not sure others will care but I just wanted to share this because if you're intimidated by using Antigravity or trying to develop your own app, it's absolutely doable!

So, I got this test. There is this Polish movie “Czas Surferow” which is like a comedy that tries to mimic some of the Quentin Tarantino ideas. It’s a funny movie, I like it as a guilty pleasure.

The important piece here is how the plot is presented on the screen. It’s going back and forth in time so we see it on the screen in order that is not chronological.

Every time new LLM model comes out I’m giving it that simple test - “give me plot of that movie in chronological order”

I’m testing different models like this since Opus 4.8. I can actually see the new models making less mistakes, hallucinating less. Recent Astra and Opus 5.5 almost nailed it 100%.

So… I gave it to Argon and it responded with 100% confidence giving me:

- kinda correct order of events
- ton of events totally made up
- made up names of actors playing character roles
- made up characters in the movie

Then I told it it’s hallucinated. It right away apologized and the hallucinated even weirder answer. I told it that it’s still made up and pointed some of the actors definitely not playing in that movie - it apologized again, figured out new even weirder answer and still stuck to same incorrect actor names.

Just so you know the absurd level - movie is about a group of not so smart guys kidnapping a businessman for a ransom. It all happens in Poland.

Argon’s plot was them along with character from totally different Polish comedy stealing a chihuahua dog and then running away to Venezuela.

Not rating the model in here as this is just one test. Just saying - be careful, cause that is GPT 3 level of hallucination here and it might be harmful.

Asking a single, straightforward question eats 5% of your session allowance on the Pro plan. Meanwhile, over on Claude, running the exact same prompt on Opus uses less than 1%.

And before the usual replies roll in saying "you shouldn't use Gemini 4 for simple tasks, just switch to Flash": that is like buying a flagship phone and being told you have to manually go into settings and throttle your CPU down to 10% every time you send a text message, otherwise the phone dies in 20 minutes. Yes, a low power chip gets the job done for a text, but you are paying for a premium experience.

Wtf google. That's 7 basic prompts across 3 chats.

All asking Argon (medium) questions like, create me a diet plan, here's my height and weight, find coffee beans that match this taste profile in my area, and recommend me mods for a popular video game that I play.

Still praying for Pro users

This will allow Pro plans (even with promotions) to access and use Gemini 4 Argon on harnesses like Clade Code , Opencode , Deepseek harnesses.

Star the repo if it helped you guys and yeah this is not absolutely perfect I have things left to fix and work on but this is a usable checkpoint for now. And Oorty at its current stage lacks the Laya pocket server addon but I have developed in and will release it in few weeks after polishing it. You can test Oorty too.

Honestly, I get that with limited resources they can't offer the models like they used to. In a situation like this, they have no choice but to kick out the freeriders. The problem is that right now, Google is screwing over Pro users too. With these kinds of limits and performance, I'd rather just use Claude.

Based on my own tests, it’s not as capable as Astra 6 or Opus 5.5 for large tasks and multi-step work. Still, for a day-to-day model, it’s great. Much more intuitive than anything ChatGPT and Claude puts out, and retains the biggest strength of Gemini’s models, which is alignment. That said, the usage limits are atrocious, and undermines a model that would otherwise have had a good chance at bringing Gemini back to relevance. In terms of capability, I would place the current Argon model at around GPT 6 sol, and yet it takes up far more of the usage limit than Astra or Opus on an equivalent plan. Keep in mind ChatGPT plus allows for *unlimited* use of GPT 6 sol on chat.

It sucks because as I said, I do believe Gemini models have much better alignment than any of the other models out there, and Argon seems like it would be genuinely good for those everyday tasks. Unfortunately, right now it exists in the messy middle of too expensive but not capable enough to be practical for any use case.

google's bullsh*t

I've been benchmarking AI models I have access to on OpenCode, Antigravity and Codex, on the same set of three reverse engineering tasks, comparing mainly their performance and execution times; basically for a project I've been making for a couple of weeks now.

Today I decided to give Gemini 4 Argon High a try; I thought it would finish fairly quickly while spending a good amount of my quota, and well, it surprised me.

It exhausted my entire 5-hour usage window in 31 minutes. It consumed 20% of my MONTHLY quota in that single attempt. It used around 900k tokens without delivering a single completed task or even a progress report; which makes me think it got stuck at the beginning of them or something.

Here are the token consumption of other models running the same home-made benchmark.

Most models didn't even reach 400k tokens, and all of these completed the task, most of them in less than 30 minutes, being only Qwen 3.8 Flash Medium, DeepSeek V4.1 Flash Max and GLM 5.3 Flash High the ones that took more to complete it.

There are two more models I tested that did get stuck in loops. Step 5 and MiMo V2.6 Pro both seemed to get stuck and failed to finish the benchmark, but their token consumption remained around 300k before they were disqualified after hitting the 75 minutes limit. MiMo V2.6 Pro even managed to deliver its work on tasks 1 and 2 before getting stuck on task 3; while Step 5 did not deliver anything, just like Gemini 4 Argon High, who burned almost 1M tokens for nothing.

I guess I could try Gemini 4 Argon Medium and Low later to see if it behaves better. In 5 hours of course; although considering it also burnt 40% of my weekly quota and that I'm now at 68%, maybe it would even complete the task again. But I'm not convinced it'll justify its cost, which, by the way, is already subsidized by OpenCode, yeah, it would be even more expensive without it.

And it's with 3.8 FLASH on MEDIUM. (PRO user)

If I had used ARGON, I can understand it, but with 3.8 FLASH on MEDIUM and with just 2 damn images!??

Greed made Google lose its mind...🖕

So the thing is when that gemini 3.x (i don't remember the exact version) was launched, it was a big update too as ppl were really waiting for a new update (the old member must remember)...
That time too using the pro mode (high mode of now) was so limit consuming that just using the pro mode for 2-3 times would finish up your daily limits... but later as we all know how thing have changed, the limits were pretty good these days

So I would say I hope this happens the same for ARGON too, coz for now using argon for 5-6 times uses the limit completely...
This is the message for someone who has never seen this type of limit usage by gemini...

I'm already down to 70% after half a day of using it. Claude ultra and opus 5.5 with sonnet is just miles ahead in terms of performance + usage.

I’ve been testing Gemini against some internal project documentation and the biggest issue I keep running into is stale context. The answer will sound completely reasonable but then I realize it pulled from something that changed a few weeks ago. Our docs are in Mintlify and stay in Git, so keeping the source updated isn’t really the problem. I’m more wondering how people are feeding documentation into Gemini so it consistently prefers the latest version. Are you using a custom RAG setup, Gemini API file search, MCP or something else? I’m mainly trying to avoid manually reuploading docs every time something changes.

I'm a casual user, i mainly use the main applications the platforms give. Claude, Gemini, ChatGPT. And Gemini's biggest problem is the app. Inside of it the models seem completely dumb, doesn't matter how capable they are. They seem to be in economy mode.

Ask something, even to argon, it will default to training data instead of doing an online research.

DARE saying the word "image" or a synonym in a prompt and it will try to generate one ignoring any other context.

Also here in europe we don't have any agentic capabilities of any type in gemini, but that's another sad story.

The other apps seem to sqeeze all they can from their models, gemini seems to be doing the opposite. And I now it can do better in AI studio for example...

Anybody else having the same experience?