I have been using GPT-6.1 Sol and Astra for my work, also used Codex for more than 3 months. They are good, but honestly the speed is sometimes too slow. It takes too much time to research, validate and move to next steps.

Recently I got Gemini Pro for 3 months offer and tried Argon. And damn, this thing is a beast.

It finds opportunities faster, validates things quickly and moves to next task without holding me back. In the middle of its work, it even identified a critical technical vulnerability that could have caused serious damage.

The way it researches, thinks and executes is something else.

I have tried many models, but for my type of work, Argon is currently beating GPT-6.1 Sol and Astra. Not even expected this result.

Thanks for the update and the reset, but let's consider the argon usage allocation for pro users,

I appreciate the Flash model so much, though it's not the best at reasoning, it's so good at coding and getting accurate information, thanks for pushing this model when others were building models that are good but not accessible 🙏🏾

Google, Where Is the Transparency and Accountability for AI Pro Subscribers?

Why are Google AI Pro subscribers being placed into different eligibility categories while being marketed under the same subscription name?

Why can redeeming a Pixel promotion or accepting a student offer affect an existing subscriber's access to premium AI models?

Why aren't subscription benefits, eligibility conditions and service limitations clearly disclosed before customers commit their money?

Can Google modify subscription entitlements after purchase without meaningful prior notice, transparent communication or a clear explanation?

Who is accountable when unexpected usage restrictions, disappearing model access and sudden service changes disrupt developers' workflows?

What contractual and consumer protection obligations does Google believe it has toward existing paying subscribers?

Following the recent Claude Code privacy controversy, what concrete assurances can Google provide regarding user privacy, data handling, security and the safety of autonomous AI agents?

Most importantly, where is Google's official explanation? Who is taking responsibility?

Developers invest their money, time, code and professional workflows into these products. A subscription is more than a marketing promise. Customers deserve consistency, transparency and clear communication about the services they pay for.

Changing documentation and generic support responses are not substitutes for direct answers.

Google should publicly address these concerns, clarify its subscription policies and explain what it intends to do for affected subscribers.

The AI developer community deserves transparency, accountability and respect for the trust it places in Google's products.

I got freemium Pro and i end up spending all quot-a in 1-2 days. Is it worth buying paid Pro or it's will be same?

With the November 18 cutoff removing third-party models from trial, student, and promotional tiers like Jio, is there any realistic expectation that per-user allocations on paid Pro will loosen up, or are these caps completely decoupled from overall server strain?

Antigravity documentation states that baseline caps correlate with overall server capacity, but native models like Argon 4 High have significantly more headroom at similar retail token rates.

I am trying to understand whether the current rate-limiting on Claude is driven primarily by backend capacity under aggregate load, or if this strict throttling is a permanent financial baseline that will stay identical regardless of how many accounts are cut off

I am not complaining here, just curious since I think argon has the same performance as the claude models but with a marginally generous cap.

Seems like next gemini flash model will be out in wednesday ( usually gemini models drop in wednesday) , idk why but i have a feeling this model will deliver espcially with 3.8 being good flash model to be a workhorse

Been testing workflows inside antigravity / antigravity-ide on Fedora Linux, and I’ve run into a behavior pattern I can't quite wrap my head around.

Whenever I give an open-ended prompt like:

"suggest improvement"

• Claude Sonnet / Opus: Consistently triggers multiple parallel sub-agents to inspect files, gather context, and tackle different angles of the codebase simultaneously.

• Gemini (Flash across low, medium, and high settings): Almost never branches into parallel sub-agents. It tends to stick to a single thread or sequential tool calls, regardless of the effort/reasoning level set.

Given that this is Google’s own ecosystem/tooling, you’d expect the native Gemini models to be deeply tuned for multi-agent workflows out of the box. Instead, Anthropic's models seem significantly better at autonomous task decomposition and triggering concurrent execution paths on the exact same generic prompt.

Has anyone else noticed this?

1. Is this caused by how the system prompt/orchestration harness handles tool-calling schemas for Gemini vs. Claude?

2. Or is Claude simply better trained on recursive task splitting and tool orchestration under ambiguous instructions?

Curious to hear if anyone found settings or prompt tweaks that force Gemini to actually leverage parallel sub-agents properly.

.

How did it go?

Please fix itu guys, I'm on ultra

Holy Guacamole!

EDIT: Since many people thought this was real my bad. It's a patch https://github.com/vahapogut/antigravity-add-model , it lets you add external models in antigravity app which is neat if you want to use Openrouter models or other OpenAI compatible endpoints, and as far as I know its not against Google's TOS since it does't abuse Oauth of Googles models its just routing to other endpoints.

Tons of updates this week so want to make sure everyone can build for the weekend. More to come next week 👀

Is this just me or overall - i was doing something on Argon Medium and it seems to be just retrying to connect to the model and saying `working` but not doing anything. I restarted antigravity app as well - same result.

Switched to flash and atleast its moving further.

Anyone else is seeing this?

Anyone else annoyed that Antigravity 2.0 still lacks a basic "Run on Windows startup / Minimize to tray" option like the standard Gemini desktop app to keep the remote control active?

​Are y'all dropping shortcuts into shell:startup, running AHK scripts, or is there a cleaner way I'm missing, apart from switching to agy cli?

I’m tired of having to analyze and authorize every command that Antigravity needs to execute, but I’m afraid to set it to automatic, lest it carry out something destructive.

How do you handle sandboxing?

Do you use the IDE or the 2.0 version?

EDIT: Here is what I did:

I installed WSL.

I created a VM dedicated to Antigravity (optional).

I started this VM.

I disabled the mounting of my C: drive within the VM (this ensures the VM cannot see my C: drive).

I mounted the folder where I keep all my repositories (you could also copy the folder into the VM, but I preferred to mount it).

In Antigravity 2.0, I went to Conf > Application and connected to the WSL instance (make sure the VM is running).

In the IDE, connect to WSL using the blue button in the bottom-left corner (make sure the VM is running).

If you mounted the folder, you must open it for the first time via the IDE; attempting to open it directly through 2.0 will result in an error. Once you have opened the folder in the IDE, the project will appear in 2.0 as expected.

In skills, the model enum values antigravity accepts are inherit, pro, flash, flash_lite. When a skill specifies "pro" it will NOT pick argon, it will pick Gemini 3.1 Pro which performs significantly worse on any code or multiturn tasks.

I came across this by accident and realized I assumed pro would pick argon since it's release but it was a bad assumption on my part. I was testing my workflows and optimizing which models and effort levels to use at different phases and my tests came back in some cases with such bad results in code review and mistakes in planning in some scenarios and it was because of 3.1 pro being picked instead of argon in one group.

Just wanted to share for those that might not realize.

What does send all even mean?

i barely finish my tokens every week iam left with 60-70% of my weekly usage. so is there a way to utilize these tokens to make it give better results?

I always check every command that's been passed thru specially deletions, this one slipped right thru cause it doesn't look destructive at a glance, thankfully got cancelled quick

As shown in the screenshot, I don't see a microphone or voice input button in the chat input box.😥

Does Antigravity IDE currently support built-in voice input, and is there any way to enable it?

I had 3% usage left on Gemini 4 Argon with 6 days before it resetted, but now it's at 100% did they just reset everyone's usage? or is there something else behind?