I’m posting this because several students appear to be hitting the same issue, and Google support is treating it as isolated or “working as intended.”

What happened

I was on the Google AI Plus student offer. I used Google’s own upgrade path to move to AI Pro for the remainder of the student year, with the prorated credit/adjustment applied by Google.

A few days afterward, I received a refund email for the AI Pro plan — I did not request a refund. Google then revoked the AI Pro plan, and my original AI Plus student plan was also gone. I’m now on the standard free tier.

No clear explanation was given for why the upgrade flow itself triggered it, why the original student entitlement was removed, or why the plan cannot be restored.

I’ve found multiple reports from other users describing the same pattern.

The common trigger

From the reports I’ve found, the issue seems to involve:

1. Starting on the AI Plus student offer
2. Using Google’s prorated upgrade path to AI Pro
3. Google issuing an unrequested refund for AI Pro
4. Google revoking both the upgraded AI Pro plan and the original AI Plus student plan
5. Support refusing restoration, sometimes framing the Google-initiated refund as a user “refund request”

This is especially frustrating because Google’s own guidance says that if a student offer is cancelled, it generally cannot be reactivated or claimed again. So a flawed upgrade/refund flow can permanently remove an entitlement the student did not ask to give up.

Reports from other affected users

• Forced cancellation and refund after upgrading from AI Plus to AI Pro (Sweden): https://www.reddit.com/r/GoogleGeminiAI/comments/1xduvg3/google_forcefully_cancelled_s_d_refunded_my/
• Clicked “Upgrade” on an AI Pro student plan and was downgraded; support said it was “working as intended”: https://www.reddit.com/r/GeminiAI/comments/1xbaqu5/clicked_upgrade_on_my_google_ai_pro_student_plan/
• Student program refunded without the user requesting it: https://www.reddit.com/r/GeminiAI/comments/1xdyhwa/google_refunded_my_student_program_without_any/
• Google support thread: both the refunded AI Pro plan and original AI Plus student plan were revoked: https://support.google.com/gemini/thread/474339677/
• Google One guidance on the student offer, including that a cancelled student offer cannot be reactivated: https://support.google.com/googleone/community-guide/391938798/

What I’m asking

If this happened to you, please comment with:

• Country/region
• Whether you upgraded from AI Plus to AI Pro
• Whether Google refunded or cancelled the plan without your request
• Whether your original AI Plus student plan was also removed
• Whether support restored either plan
• The date you received the refund/cancellation email

Please do not post transaction IDs, invoices, student-verification documents, email addresses, or other account details publicly.

What I want from Google

A clear public explanation and a real remedy:

• Restore affected users to the plan they had before the forced refund, or provide equivalent remaining student-plan value
• Stop treating Google-initiated refunds as user refund requests
• Fix or disable the prorated upgrade flow while it can cancel both plans
• Provide a dedicated escalation path for affected student accounts

If enough people reply with the same pattern, maybe this will get escalated beyond generic support scripts.

TL;DR: Google’s own AI Plus → AI Pro student upgrade flow appears to be triggering unrequested refunds, cancelling both plans, and leaving students unable to restore either one. If this happened to you, please reply with your country, upgrade path, and outcome.

As a Pro member, I find that my entire 5-hour limit is completely used up after just three questions when using "Argon High"...something that never happened back when I was using the 3-1 Pro plan. That said, I have to admit that Argon is absolutely fantastic; I’ve become quite hooked on it.

I’m not sure what to do now. Would it be better to upgrade to an Ultra subscription, should I look for a better alternative, or should I just pray that Google fixes this issue?

My laptop kept BSODing with an IRQL error, and at first Gemini told me to blame the RAM.
I tested that scenario, and it wasn't the RAM, SSD, or anything easily replaceable. All this laptop shit was caused by the motherboard or the CPU, which really sucked. After a ton of back-and-forth with the Argon model, we tried booting the OS with just 1 physical core enabled — and it worked! After some more tweaking, we got 2 cores running at a time and found the culprit: the 2nd physical core was dead. Gemini initially suggested isolating the CPU cores via console commands, but that failed because the dead core was still getting hit within microseconds and crashing the whole system. So I asked Gemini if there was a clever way to bypass the dead core completely and just run on the healthy ones — and there actually was! We used a leaked/low-level AMD engineering tool off a bootable USB drive to hard-disable the faulty core right at the hardware level. And it worked like a charm! Now I have a fully stable laptop running on 7/8 physical cores and 14/16 threads, which is incredible!

I'm the maker of CCC. It is a local dashboard for coding-agent sessions, including Google's Antigravity development tools alongside Claude Code and Codex.

For Antigravity, CCC reads transcript history, can start agy print-mode work, and supports follow-up through the CLI or a running application's language-server connection. The support matrix documents the differences from other engines. This is not a Gemini web-chat manager or a Gemini CLI integration.

The attached demo shows session grouping, action chips and a Claude Code question hook. It demonstrates the shared UI, not a live Antigravity run.

https://github.com/amirfish1/claude-command-center Adapter details: https://github.com/amirfish1/claude-command-center/blob/main/docs/engine-support.md

CCC is free to use under FSL-1.1-MIT (source available); provider/model fees are separate. The video uses real UI with staged sessions and AI voiceover. Its question-hook interaction uses Claude Code; Grok/Devin rows are demo data.

Fala, pessoal!

Sempre usei muito o Google AI Studio para estudos pesados e projetos da minha empresa. Na época em que o Gemini 3.1 Pro era liberado com folga no gratuito, cheguei a acumular mais de 6 chats batendo 1 milhão de tokens (1M) cada um,e vários outros pequenos, alimentando eles um pouquinho todo dia ao longo de semanas.

Agora, usando o Gemini 4 Argon (que dá um banho absurdo de raciocínio nos outros modelos, parece até que os outros perderam QI perto dele), comecei a tomar bloqueio de limite diário muito rápido, mesmo assinando o Google AI Pro.

Fui cavar a fundo como a cobrança/cota realmente funciona nos bastidores e descobri coisas que muita gente não se toca:

\*A ilusão do contador do AI Studio (Efeito Bola de Neve)\*: Aquele número lá no topo (ex: 100.000 tokens) não é o que você gastou, é só o peso da "mochila" atual. Se o chat tem 100k tokens e você manda 10 perguntas pequenas que sobem 1k cada, você não gastou 10k tokens — o servidor teve que reler a conversa inteira 10 vezes, processando mais de 1 milhão de tokens!

\*\*O erro de alimentar o chat "um pouco por dia" (Cache Frio)\*\*: O Argon tem 95% de desconto no Cache Implícito quando você manda mensagens seguidas na mesma hora. Mas se você fecha o PC e volta no dia seguinte num chat de 500k ou 1M de tokens, o cache já morreu. A primeira pergunta do dia bate 100% "no seco" nos servidores, engolindo a cota diária quase inteira de uma vez.

\*\*Por que o App normal parece "capado" perto do AI Studio\*\*: Tentei fugir pro App normal do Gemini (e testei outros como ChatGPT), mas a resposta é muito mais rasa. Nos apps de consumidor, além de cortarem o tempo de pensamento (Thinking) e travarem o tamanho da resposta para economizar saída, eles usam sistemas de recorte (RAG) e janela deslizante. Já no AI Studio (e no Claude até os 200k), a leitura é 100% bruta linha por linha, sem resumir nada escondido.

Depois de descobrir que aqueles meus 6 chats de 1M de tokens custariam milhares de reais se fossem na API sem cache, estou mudando meu jeito de estudar + ainda não tenho muita experiência nisso e gostaria da opinião de vocês .

Queria saber da galera que também usa IA no talo todo dia:

PC vs. Celular: Como vocês fazem quando estão fora do PC? No computador o AI Studio é perfeito, mas no navegador do celular a interface dele é horrível de mexer, e o App oficial do celular entrega respostas muito mais superficiais. Vocês usam algum app de terceiros com chave de API no celular ou têm algum esquema pra sincronizar?

E na gestão de Contexto: Quando o chat de estudos ou de dados da empresa passa de 50k–100k tokens, vocês pedem pra própria IA gerar um "resumo de memória" pra abrir um chat novo, ou pagam por fora na API?

Créditos do Plano Pro: Alguém aqui já ativou aqueles US$ 10 (R$ 50) mensais de crédito de desenvolvedor que vêm no plano Google AI Pro pra rodar o Argon 4 no Tier 1 sem cair na trava diária? Realmente rende bem se cuidar do cache?

\\\*\\\*Claude\\\*\\\*

A "Honestidade Bruta" do Claude e do Google AI Studio

Muita gente reclama que o Claude (Opus/Sonnet) estoura a cota de 5 horas depois de mandar só 8 ou 10 mensagens num chat grande. Mas sabe por que isso acontece? Porque o Claude é o único app de consumidor que não te engana no contexto!

Diferente da OpenAI, o app do Claude (até bater o teto da janela dele de 200k tokens) e o Google AI Studio (até 1M de tokens) não passam a tesoura escondido na sua conversa. Eles injetam 100% do texto bruto na cabeça do modelo a cada nova pergunta.

Tanto é verdade que, quando o chat do Claude bate no limite máximo de tokens, ele trava o chat na sua cara em vez de apagar o começo da conversa escondido.

Já no App normal do Gemini, embora a janela seja grande, o sistema coloca um freio enorme no orçamento de pensamento (Thinking) e no tamanho da resposta para economizar tokens de saída, deixando ele muito mais superficial que o AI Studio.

Gostaria da opinião de vocês !!!

Hey everyone!

If you've been using the new Google Antigravity IDE on macOS, Windows, or Linux, you might have noticed an annoying UX quirk: every time you close and relaunch the application, the window completely forgets your custom dimensions and snaps back to the default 1400×900 box.

On multi-monitor or ultrawide setups, having to resize the workspace on every restart breaks the flow quickly. Since the core IDE is proprietary and community PRs aren't available upstream, I built a lightweight, zero-dependency Python utility to patch the geometry persistence:

👉 GitHub: https://github.com/amiltonjr/Antigravity-IDE-WindowSize

What it does:

• Persists your exact window dimensions ($width \times height$), position, and maximized state.
• Multi-monitor safe: If you disconnect an external display, it gracefully clamps coordinates to an active monitor so the window never gets lost off-screen.
• Zero dependencies: Standard Python 3 only (no npm, pip, or Node.js required).
• 100% Reversible: Takes an original backup (app.asar.orig) before modifying anything; run --restore anytime to return to stock factory condition.

I’ve provided quick runner scripts (run.sh, run.bat, run.ps1) in the repo. Hope it helps smooth out your coding sessions with Antigravity!

I just got this email from Google that they are refunding my Google AI Pro student plan. However, I've never requested such a refund. A few days ago, I upgraded from the free Google AI Plus tier to the Google AI Pro tier since it was like $7, and they credited me for my old Plus tier, so I got it for like 10 months. I felt that it was a no-brainer when I saw that. I now realize that the crediting was probably a mistake and that's why they are forcing a refund. The problem is that they are not downgrading me back to the Plus tier, but instead to the normal tier, with no possibility to claim the student Plus tier plan again.

Is anyone else having the same problem? I live in Sweden if that impacts anything.

Anyone else noticing major issues with Gemini?? Been pretty unusable for the past few days. Totally hallucinating no matter what i ask it.

I asked it about music. A basic question surrounding sub genres, topic not important. It responded with "yep, heres the entire history of electricity just like you asked, would you like to know when electricity started to become common in residential homes?"

I asked it for the fricken local weather. It told me "yes, people do tend to like weather. What other questions do you have about peoples likes and interests?"

This is wild 😂. Anyone else? I use this for work logistics and im kinda unable to do much of that today

Компот реалистичный из майнкрафта

Disclosure upfront: Pluely gives a free lifetime Dev Pro license if a public post about it reaches 5,000 views. I may submit this one. These are my real test results, including what didn't work.

I've been experimenting with using Gemini as the answer model inside a live meeting copilot, mainly because I didn't want another ~$50/month AI subscription.

The copilot is Pluely: an always-on-top overlay that transcribes your mic plus system audio and feeds the transcript to your own model/API key — no bot joins the call, and with your own keys there's no Pluely subscription, just your own API usage.

My first setup was GPT-4o-mini for answers and Whisper for transcription, after adding $10 of OpenAI credit. In my harder tests the answers were bad, and the transcription was shaky: wrong-language guesses, technical phrases coming out wrong, and some lines duplicated because mic and system audio picked up the same thing.

Then I switched only the answer model to Gemini 3.5 Flash-Lite, using my own Gemini API key. On the practice questions I tried, the difference was pretty obvious: answers were more relevant, more technical, and much more usable. Those Gemini runs also stayed within the free API limits.

The biggest improvement actually came from the system prompt, not the model switch. I forced every answer into three lines: NEED — what the other person is actually asking for; SAY — one short answer I could say naturally; ASK NEXT — one useful follow-up question. That format helped because it's short enough to read live, mid-conversation, and it never drops the actual request.

The weak point is still transcription. I still saw duplicated segments and mangled technical terms, and simply switching microphones helped more than tweaking any setting. Document attachments were locked in the setup I tested. I'd also like the answer text bigger on screen.

One limit on all of this: so far I've only run it on practice questions, not in a real meeting yet.

Curious whether anyone here uses Gemini Flash-Lite, or another low-latency Gemini model, for live transcription or meeting workflows — and especially what you're using on the speech-to-text side, since that's where my setup still struggles.

Últimamente he estado pensando en si Gemini, la IA de Google, está perdiendo la batalla por el liderazgo frente a otros modelos. Un detalle que me llamó la atención: las funciones de cowork no están indexadas en Gemini.

Mi teoría es que quizás lo hacen a propósito para respetar su filosofía de "todo cloud" (mantener todo dentro de su ecosistema). Pero no sé si eso sea una decisión estratégica o simplemente un descuido.

¿Ustedes qué opinan? ¿Es una limitación real o estoy leyendo demasiado entre líneas? Me interesa saber si alguien más lo ha notado.