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I built AG2R (Antigravity 2.0 Remote) — a lightweight mobile interface that lets you monitor and interact with your Antigravity AI coding sessions from your phone. It mirrors Antigravity's UI in real time via Chrome DevTools Protocol (CDP), so you can watch your agent work, approve permissions, review code changes, and send messages — all without walking back to your desk.

It's fully open source (MIT), self-hosted, and works on Wi-Fi, hotspot, or anywhere in the world via a tunnel of your choice.

GitHub: https://github.com/the-future-company/ag2r

What it does

AG2R connects to your running Antigravity instance via CDP and captures the live DOM — chat messages, code diffs, permission dialogs, sidebar state — then streams it to your phone through WebSockets. It's a bridge, not a reconstruction. What you see on your phone is exactly what's on your desktop, rendered faithfully with all markdown, code blocks, and formatting intact.

Features

📡 Real-time Chat Monitoring

Watch the agent's responses stream in as they happen. Code blocks, markdown formatting, and all rich content render exactly as they appear on desktop.

🔐 Remote Permission Handling

Approve, deny, or skip permission requests right from your phone. Select an option, hit Submit, and the agent continues — no need to walk back to your computer. Push notifications alert you when a permission is waiting.

📝 Code Review

Browse modified files, view diffs, and navigate between Overview and Review tabs — all on mobile. Full syntax-highlighted diffs, just like on desktop.

💬 Send Messages & Voice Input

Type and send messages to the AI from your phone with a native mobile keyboard. Or dictate messages using the built-in voice input (microphone button). You can also attach images — take a photo or pick from your gallery and send it alongside your message.

🗂️ Sidebar & Conversation Navigation

Switch between conversations, browse artifacts, view background tasks, and navigate the full sidebar — all captured directly from Antigravity's UI.

🔔 Push Notifications (PWA)

Get notified on your phone when a session needs attention (permission approvals, agent questions). Tap the notification to jump straight to the pending request. Works on both iOS (via Add to Home Screen, iOS 16.4+) and Android.

🤖 Subagent Support

View subagent conversations with a dedicated back-navigation bar. See which subagents are running, navigate into them, and return to the parent conversation.

💬 Commenting System

Select text on any document in the review panel, leave comments with context (captured as quoted selections + your annotation), and queue them for batch sending. Review, edit, or delete queued comments before sending them all at once.

⏱️ Scheduled Tasks & Running Tasks

View running background tasks with an expandable strip at the bottom. Manage scheduled tasks through a full-screen overlay — create, edit, and interact with AG's scheduler UI from mobile.

⏹️ Stop Generation

Cancel a running generation with a single tap on the stop button.

🔄 Auto-Reconnect

Seamless reconnection when the connection drops — whether you switch apps, lose signal, or lock your phone.

🖥️ Desktop & Tablet Support

Not just for phones — AG2R works great on tablets and even secondary desktop browsers.

🌐 Access from Anywhere

Three connectivity options:

• Local network — same Wi-Fi, no setup needed
• Quick tunnel — use any tunneling software (Cloudflare, ngrok, Tailscale, etc.) for instant remote access
• Custom domain — permanent URL with your own domain for a stable endpoint

🔒 Authentication

Optional password protection with cookie-based auth (stays logged in for 30 days). Magic link support (?key=password) for easy device setup. Required when exposing to the internet.

🔁 Watchdog & Auto-Update

A watchdog script keeps AG2R running 24/7 — detects new commits, pulls updates, and restarts the server automatically. Add it to cron and forget about it.

MIT licensed. https://github.com/the-future-company/ag2r

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Guys Do you think this is Okay?

I moved from VSCode to Antigravity about 6 months ago and haven’t looked back. It’s been a solid driver for my development across TypeScript, JavaScript, Python, and some fairly complex HTML. The latest IDE update has been working well.

I was originally holding off on Antigravity 2.0 because I have other tools for "vibe coding" and non-coding tasks, but I finally installed it last week and I'm really impressed. It has effectively become my primary interface for almost everything else now.

A few notes on how I’m running it:

*Orchestration: I’ve configured both 2.0 and the IDE to use Gemini for local LLM orchestration. It handles my local LLM (Gemma-4 31b mostly) surprisingly well when I offload specific tasks to it.

*Model Selection: Gemini 3.5 medium is my new workhorse for code, moderate architecture, planning and spec writing. I only bump up to "high" if I hit a complex blocker or to review architecture details and plans. I've also been happy with how capable 3.1 low and flash are —they’re my go-to for light-duty tasks to keep token usage minimal and fast.

*Tool Calling: I haven't pushed this with a massive number of external tools like some of you, but for my current stack, it’s been rock solid.

For anyone on the fence or just starting out with the 2.0 update, it’s definitely worth trying out.

I’m curious—how are others handling their model-switching workflow between the 3.5 series and smaller models? Also, for those of you running local models alongside Gemini, what’s your strategy for balancing the two? I’m currently leaning on Gemma-4 31b for specific tasks (including coding), but I’d love to hear how you’re optimizing your local-to-cloud hand-offs.

Hey,

I'm using antigravity IDE/antigravity CLI with Google AI Pro for modular code and simple web apps. My work relies on analyzing a massive amount of code, but since the recent update, I keep running out of context capacity extremely fast. Once the chat version cutoff triggers, it becomes completely impossible to feed such a large number of modular files into the prompt.

Instead of switching tools, I want to optimize how I actually work.

What is a more effective workflow for handling split codebases within these strict text constraints? How do you provide context and analyze large projects with the AI without burning through the available message space instantly?

How are you guys saving tokens?

I have the AI Pro subscription and usually follow this workflow in the Antigravity 2.0 GUI:
1 - Chat with Claude Opus for architecture and planning
2 - Chat with Gemini Flash 3.5 High for development

After the updates, Google messed up these models usage and it got pretty bad. How are you handling this on your end? Looking for real experiences.

I noticed when i ask AG to use subagents to audit my project, sometimes it does not do that.

Is there a way to force it to only use subagents for certain tasks?

1. Uhh!! My usage ended nooo, google bad, moving to codex cursor

2. Uh excuse me guyz why is my gemini stuck in loop, why is it so dumb bad, google models suckkk

3. Well things are finally stable now, hope they remain so

4. They ruined it again!!!!

5. Stop posting the same complaint slop, this subreddit sucks!

6. Posts about this sub in a nutshell

So at the launch it was kinda like sonnet but nowadays it's just trash

Antigravity IDE is quite good on its own. However, the Gemini model is clearly lagging behind in terms of coding. The Opus model has not received any new updates either, and the amount is too small.

Why not release the BYOK capability? This way, everyone can freely choose the model they like.

its clear that the models are out dated but is there anu clue on when they will provide the new models ?

We’ve all noticed the dead silence coming out of Mountain View lately. Google dropped Gemini 3.5 Flash back in May, dropped heavy hints that the Pro version would follow right behind it... and since then, absolute crickets. Nothing on Vertex, nothing on AI Studio. In the 2026 AI timeline, a few months of delay feels like an absolute eternity.

If you're wondering why the most anticipated model in the ecosystem is still desperately MIA, relax: it's not a simple engineering hiccup. It's a full-blown existential crisis—strategic, human, and financial. Let’s look under the hood to see what’s actually paralyzing Google.

1. The "Game Over" Syndrome: Why the original 3.5 Pro was dead on arrival

The first hurdle is pure competitive pressure. Gemini 3.5 Pro was originally calibrated to tackle early-2026 benchmarks (like Claude Opus 4.7). But in the meantime, the competition completely shattered the glass ceiling by surprise-dropping Claude Fable 5 / Mythos 5 (Anthropic) and GPT-5.6 Sol (OpenAI) at the end of June.

For Google, the situation turned dangerously binary:

• The Benchmark Trap: If Google rolls out 3.5 Pro as originally spec'd and it gets absolutely humiliated on complex coding or raw reasoning by Sol or Fable, it's an immediate tailspin for Alphabet stock (GOOGL). The market has zero patience left for the tech giant's foot-dragging.
• The "Thanos" Hypothesis: To avoid a PR disaster, Google was forced to pull the model back into the pre-training factory. They either have to aggressively bake in advanced Reasoning techniques (native chain-of-thought at inference time) to artificially spike its algorithmic IQ, or they are brewing a massive architectural pivot—some kind of "Gemini 3.5 Thanos" 😅—to avoid wasting their flagship card. They simply cannot afford to ship a top-tier variant that can't look the competition dead in the eye.

2. The Organizational Bug: Forcing theoretical physicists to build assembly lines

The second issue targets the very DNA of DeepMind. Historically, DeepMind is the final boss of foundational AI research. They literally invented the modern world: Transformers (2017), attention mechanisms, AlphaFold, structural computing. They sit on the Holy Grail of AI intellectual property.

The problem? A catastrophic structural disconnect between pure research and product engineering.

• The Missing Link: You can't ask the brightest minds in mathematical science to spend their days fine-tuning censorship guardrails for a consumer chatbot, packaging extensions for Google Workspace, or optimizing server costs for Google Docs. There is a total lack of "technical translators"—applied research teams—capable of transforming a theoretical breakthrough into a stable product without frustrating the researchers.
• The Brain Drain: Forcing these geniuses into product optimization has triggered massive internal burnout. Just this past June, the talent drain reached historic proportions: Noam Shazeer (co-author of the original Transformers paper) split back to OpenAI to focus on pure architecture research, John Jumper (the Nobel laureate behind AlphaFold) migrated to Anthropic, and Denny Zhou headed to Meta. When your core brains walk out because they refuse to watch their discoveries rot in a drawer or get throttled by corporate bureaucracy, your raw innovation engine stalls.

3. The Innovator’s Dilemma: The Ad-Revenue Suicide Pact 📉🍔

Finally, there's the economic brick wall. Unlike OpenAI, which doesn't care about burning VC cash, or Meta, which uses AI to hook user attention on social feeds, Google is a prisoner of its own money-printing machine: traditional search and those sacred "blue links."

• The Impossible Equation: Google wants a model that is "Ultra-Powerful, Fast, and Affordable"—the ultimate engineering trilemma. They want to ship it to billions of Android phones and Workspace accounts. But an advanced AI query costs 10x to 20x more in electricity and TPUs than a legacy search run, all while wiping out clicks on sponsored ads. The more powerful Google makes its B2C AI, the more it cannibalizes its own golden ad margins.
• The Strategic Procrastinator: This is Google’s historical reflex. Unlike Meta, which open-sources weights aggressively so the community can clean up and optimize their code for free, Google panics at the thought of launching an imperfect, buggy product that could tank its institutional brand image. Their strategy has become to let agile startups eat the initial dirt, test the market with buggy tools, and take the PR hits. Once the market matures, Google rolls up late to the party—but with a massive, industrial TPU infrastructure hammer to crush serving costs and scale it everywhere.

The Verdict

Google is locked inside a gilded cage. They have the raw compute power and they literally invented the core tech, but they are driving with the emergency brake fully engaged because their own invention is a direct threat to their legacy business model. They won't unleash Gemini 3.5 Pro until they find a way to make it economically viable at global scale, or technically beefy enough to decapitate GPT Sol.

Until then, we’ll keep writing our scripts and running our loops on Flash or competitor APIs. At least Flash gets the job done cheaply while we wait for the big brother to finally wake up from Mountain View’s corporate coma 🤫.

Context: I am using antigravity CLI version, Gemini 3.5 Flash High thinking business license.

In a previous comment, I mentioned that while Antigravity CLI has planning mode, it doesn’t work well, often i have no chance to read/ review the plan before execution. But since I have to use antigravity at work, i have been experimenting. And to my surprise, agy works really well with Superpowers planning skill. You have to call the skill directly using “/“ so from that perspective it is not as intuitive as codex or claude , but hey, it works.

The plan is good and it’s saved , the code-review after makes it better. So now i have a working flow vs before.

Anyone else has similar tips/tricks to share

P.S: personally i am using codex, opencode (main driver) and a little bit of claude.

Which would be the best approach ?

I was regretting paying for a year of Google AI Pro because Antigravity was not stable. i trashed Google, so now I have to give them their props because it's finally stable now and the IDE is usable. Running version 2.2.1 on Win11.

The value is only okay if coding was the only reason I got it for, but it saved me some money because it comes with YouTube Premium Lite, and I was subscribed to that, and it has 50GB of storage, and I can drop a $30 annual subscription and move my files to Drive. Not sure i will renew, though.

Using Minimax in Opencode is performing better than Flash 3.5 in the Antigravity IDE, and the Minimax tokens don't run out even on the ten-dollar plan. I would really like it if Google allowed using my plan in Opencode, like OpenAI, Minimax, Kimi, etc do. Flash would perform well as part of some agents I use.

hello guys , is gemma 4 free via the ai studio api ?

I am working with antigravity. I want to create a system wherein i type the name of the company and the ai/agent fetches all the concalls/annual reports numbers etc. Then info gets feeded into LLM for further analysis. Analysis step would be customised according to my requirement. What i want to analyse and how should it display results will be customised by me. In future i want to add 2 LLM for last process. I have absolutely no clue how to go by this. I’m learning so not familiar with other technical terms.

I’m currently a super happy user of the Google Antigravity Pro plan. Honestly, it’s been amazing I’ve already built so many apps with it, and the package inclusions (like the 5TB Google Drive) are incredibly generous. Big shoutout and thank you to Google Team and Gemini Team!!!

That said, I keep seeing a lot of buzz around Claude Code (Fable 5) and I'm a bit curious about how it plays with Antigravity. I have a couple of questions for anyone who has tried both:

1. Model Access: If I subscribe to Claude Code ($20/mo or $100/mo), does that subscription somehow cross over or let me use the latest Claude models inside Antigravity? Or are they completely separate billing systems?
2. Qu-ota / Lim-its: If they do link up (or if you just use them side-by-side Google Ai Ultra vs Claude Max or even the $20 tier), how generous are the Claude Code lim its compared to what we get with Gemini Flash (medium/high usage) on a daily or weekly basis? I know Antigravity allows a /model switch, but I'm trying to figure out if paying Anthropic directly changes the lim its inside the Google ecosystem or if it's just for their native CLI.

I definitely plan to continue using my Antigravity plan and upgrade to Ultra IF only 3.5 Pro is good because it has been a beast for my workflow, but I'd love to know if adding Claude Code to my toolkit is worth it or if it just complicates things. similar question to codex vs antigravity

Thanks in advance for any insights!

Hi everyone,

I’m trying to use Antigravity IDE Remote SSH with an HPC cluster (Ada), but I’m stuck during the remote server installation.

My setup

• OS: macOS Sequoia (Apple Silicon)
• Antigravity IDE: 2.1.1
• VSCode OSS: 1.107.0
• Commit: e0b7a2bcf575cfba10528c4e7c10bd3ce2d7769a
• Remote machine: Ubuntu 18.04 (GLIBC 2.17)
• SSH works perfectly.

I can:

• SSH into the login node (ada)
• Start an interactive Slurm job
• SSH into the allocated compute node (gnode)
• Internet works from the compute node (wget https://google.com succeeds)

The only thing failing is Antigravity’s remote server installation.

What happens

When Antigravity tries to install the remote server, it downloads from:

https://redirector.gvt1.com/...

The redirects look like this:

redirector.gvt1.com
    ↓
r2---sn-ci5gup-itqd.gvt1.com
    ↓
r4---sn-h5576nsy.gvt1.com
    ↓
r5---sn-ojnpo5-5b.gvt1.com

The final server responds with:

404 Not Found

So the server binary is never downloaded.

What’s confusing

Running:

curl -I -L https://redirector.gvt1.com/...

ends with:

HTTP/1.1 200 OK
Content-Length: 109143791

which suggests the file exists.

However, actually downloading it with either:

curl -L -O ...

or

wget ...

always ends with:

404 Not Found

from the final Google CDN server.

Things I’ve already tried

• Different Wi-Fi network
• Mobile hotspot
• IIIT network
• IPv4 only (curl -4)
• HTTP/1.1 (curl --http1.1)
• wget
• curl
• Manual browser download
• Downloading from both my local machine and the remote cluster

The final Google CDN endpoint always returns a 404.

Cluster details

• SSH works normally.
• Remote shell works.
• Slurm jobs work.
• Compute node has internet access.
• This doesn’t seem to be an SSH issue.
• It doesn’t appear to be a firewall issue either because normal HTTPS traffic works.

My questions

1. Has anyone else seen Antigravity fail because the Google CDN redirects to a non-existent edge cache?
2. Is there an official offline installation method for the Antigravity remote server?
3. Can the remote server tarball be downloaded manually and copied into ~/.antigravity-ide-server/ like VS Code Server?
4. Is there a way to force Antigravity to use another download mirror instead of the broken Google CDN node?

I’d really appreciate any suggestions. At the moment, VS Code Remote SSH works fine, but I’d prefer using Antigravity if there’s a workaround.

Thanks!