Google's secret AI model "DRAGONTAIL" is scary good...

The AI world is buzzing, and it looks like Google is making a serious play to reclaim the top spot, going far beyond its already impressive Gemini 2.5 Pro. We're hearing whispers of incredibly potent "stealth" models like Dragon Tail and Night Whisper, which are supposedly excelling in areas like coding and web development. This signals a major comeback for Google, as they leverage their immense resources, top-tier talent, and even their own custom hardware to push the boundaries of AI.

Here’s a breakdown of what’s happening:

The Shifting AI Leaderboard & New Model Rumors

• While Gemini 2.5 Pro is currently dominating AI leaderboards, this is really just the "tip of the iceberg." There are a lot of big moves happening behind the scenes.
• DeepSeek is rumored to be on the verge of releasing a new model, possibly called "R2." This one is supposedly a reasoning model with a knack for coding. I'm really curious to see if R2 can deliver on that coding promise.
• OpenAI isn't staying quiet either. Sam Altman dropped hints about a stealth model named "Quasar," described as "very good." This could be some version of their next big thing (O3, O4 Mini, etc.), but it's all hush-hush for now. Sam's teases always get the community excited!
• Google's Secret Arsenal: Beyond the publicly known Gemini, Google is apparently cooking up a whole series of unreleased models. These are still in "stealth mode," with names like Night Whisper, Dream Tides, Moon Howler, Dragon Tail, Stargazer, Shadebrook, and River Hollow popping up in online discussions. It sounds like a lineup of superheroes, but for AI!

Spotlight on Google's "Dragon Tail" and "Night Whisper"

• Dragon Tail: This unreleased Google model is the talk of the town, with rumors suggesting it's outperforming even Gemini 2.5 Pro in web development.
  • It's getting high praise for its coding skills, especially for front-end design and quickly generating attractive, functional landing pages.
  • I feel that even though these are rumors, the sheer volume of positive chatter from different sources makes Dragon Tail one to watch.
• Night Whisper: Another rumored Google model that's making waves.
  • When outputs allegedly from Night Whisper are compared to Gemini 2.5 Pro for web design, Night Whisper's creations look more "refined" and "modern."
  • My personal taste leans towards Night Whisper's design style; it just has a cleaner, more professional webpage feel, though color schemes can be a personal thing.
  • In one comparison, Night Whisper apparently outperformed Cloud 3.7 in generating a 3D calendar, showing its potential.
• Overall Vibe: It feels like these stealth Google models are shaping up to be at least as good as Gemini 2.5 Pro, and potentially much better in specialized areas like coding. I'm genuinely excited to see if they live up to the hype when they're officially unveiled.

The Role of Chatbot Arena in Testing New Models

• Chatbot Arena is a cool platform where you can compare two AI models side-by-side without knowing which is which. You give a prompt, get two answers, and then vote for your favorite.
• These new, unreleased "stealth models" from Google, Anthropic, OpenAI, etc., often get secretly added to Chatbot Arena for real-world testing.
  • This gives their creators valuable, unbiased feedback and a chance to see how they stack up against competitors.
• I gave it a go:
  • I asked for a "Minesweeper website with fancy graphics." Model A (which turned out to be DeepSeek R1) did an amazing job with great graphics, while Model B completely failed. DeepSeek R1 really impressed me there.
  • On another try with the same prompt, Model A (later revealed as River Hollow, one of the rumored Google models) was "excellent" – the best Minesweeper version I'd seen from an AI. It looked great and worked!
• My understanding is that you can't pick these hidden models directly. They appear randomly to ensure the feedback is genuine and not skewed by people knowing which model they're testing.
• It makes sense that different stealth models (like Dragon Tail for coding and Night Whisper for front-end) might be specialized for different strengths.

Why AI is Increasingly Focused on Coding

• Back in the day, AI models were pretty terrible at coding; it was a bit of a gamble whether they'd get a simple script right.
• So, we mostly tested them with word problems or reasoning puzzles.
• Now that their coding skills are much better, it's actually harder to test them with text-based problems because they might have just memorized the answer if it was in their training data.
• I've found myself leaning more towards giving models complex coding tasks, like asking them to create a complete game in one go.
  • This really tests their understanding and ability to turn a request into working code. Plus, it's easy for me to see if it worked: did the program run? Did it do what I asked?
• Honestly, seeing AI generate code is also just more visually engaging and exciting than reading long blocks of text. There's more "action" on screen.
• And let's be real, the ability to automate coding is incredibly valuable economically. That's a huge reason why companies like OpenAI, Anthropic, and Google are pouring resources into AI coding tools.

Google's AI Journey: From Fumbling Lead to Renewed Dominance

• Alberto Romero from The Algorithmic Bridge really nailed the feeling many of us, myself included, had about Google's AI story.
• Google was initially seen as the clear leader in AI, with breakthroughs like DeepMind's AlphaGo and AlphaZero (remember "Move 37"? It felt like encountering an alien intelligence!).
• I, too, was a bit "low-key saddened by Google's constant fumbling" because they had all the pieces: the tech, the talent, the money, and the infrastructure.
• The most plausible reason for this hesitation? AI directly threatened Google's golden goose: search advertising revenue.
  • AI search tools like Perplexity and deep research features let users bypass traditional Google Search, where they're shown ads.
  • So, for a while, it seemed Google "didn't shoot at all," and they lost their commanding lead.
• Fast forward to now, about two and a half years after ChatGPT changed everything, and Google DeepMind is "winning pretty hard."
• It really feels like Google has decided to go "all in" on AI, and they're building and releasing new things at a rapid pace. Their momentum is building like a snowball.

Google's Current AI Prowess and Ecosystem

• Gemini 2.5 Pro Experimental: This is widely considered the best publicly available AI model in the world right now.
  • It’s consistently at the top of the LM Arena leaderboard, showing broad capabilities.
  • It's also fast, relatively cheap to use, has free access tiers, and an impressive 1 million token context window. I think most would agree it's the current champ.
• Gemini 2.5 Flash: This version is incredibly fast and cheap, even more so than DeepSeek (which was known for its cost-effectiveness).
  • It’s perfect for "edge" applications – think AI running directly on your phone, in your car, or even on smart home devices.
  • Given Google's massive Android ecosystem, the potential for integrating this into phones is huge. As an Android user, this is pretty exciting.
• A Full Suite of AI Models: Google isn't just about text; they have models for almost everything:
  • Text: The Gemini family.
  • Music: Lyria. It might not be at Suno's level yet for AI music generation, but I suspect Google is being extra careful about copyright issues. They could definitely catch up, especially if they strike deals with the music industry.
  • Image: Imogen 3 (or "Imagine 3," as Google apparently says it). It's a "solid" image generator, even if not the absolute best.
  • Video: Vio. Many people seem to think it's better than OpenAI's Sora for AI video.
  • Voice/Speech: Chirp.
  • My take: They might not be #1 in every single category, but they're leading in the all-important LLM space and are highly competitive in areas like video.
• Deep Research Mode: Their version is considered twice as good as OpenAI's similar feature.
• Ambitious Projects:
  • Project Astra: This is an AI assistant that can see and interact with the world through your camera (you can try it in AI Studio or on your phone). It's "very good."
  • Project Mariner: This is focused on AI for computer interaction, like Anthropic's models that can use software for you.
  • Expect these to be built into Chromebooks, Android phones, and other Google devices.
• AI Agents: Google is making big strides here.
  • They've developed an "Agent to Agent protocol" (like Anthropic's MCP) to standardize how different AI agents communicate.
  • They're also launching "Agent Space," which sounds like a marketplace or a "Google for AI agents." The idea is to help people find and use various specialized AI agents. It feels like they're laying the groundwork for a "Google 2.0" built on AI.
• Research and Hardware:
  • Google continues to publish a lot of influential research papers and emphasizes AI safety. Demis Hassabis and his team even won a Nobel Prize for their work on AlphaFold.
  • Crucially, Google designs its own TPUs (Tensor Processing Units) – specialized chips for AI. They've announced recent breakthroughs here, and having in-house hardware is a massive strategic advantage.

The "Google In-House Advantage"

• An interview with Google Cloud CEO Thomas Kurian really shed light on how tightly integrated their teams are. DeepMind (their AI research lab) and Google Cloud work "extraordinarily closely," even sharing the same buildings.
• Google Cloud builds the actual infrastructure (servers, networks) that DeepMind's models train and run on.
• They get new models from Demis's team daily and can make them available to developers within hours.
• There's a constant feedback loop: data from how people use the models helps to improve them through further pre-training.
• A key point is that all of Google's own services (Search, YouTube, etc.) use the same AI systems and models. This means the models learn incredibly fast from the enormous amount of real-world interaction and feedback.
• He gave an example of using Gemini for "threat hunting" in cybersecurity, which required specific tuning of the model – something made easier by this close collaboration.
• My takeaway from this: Google has its cloud platform, its world-class AI researchers (DeepMind), its own custom AI chips (TPUs), and access to unimaginable amounts of data, all under one roof. It's clear now that they weren't lacking the ability to lead in AI before; they were just hesitant because of the potential impact on their existing search business. That hesitation seems to be gone.

Firebase Studio: AI-Assisted Development Made Easy

• Google recently launched Firebase Studio, which I've started testing. It's an AI-powered coding environment, similar in spirit to tools like Cursor.
• It’s built on top of VS Code, which many developers already use.
• One of its coolest features is how easy it makes it to deploy your applications online – often with just a click or two.
• If Google keeps developing this and smoothing out the rough edges, it has the potential to be "huge."
• Right now, it's still a preview, so it can be "a little bit hard to work with" at times. Manage your expectations if you try it.
• The promise here is revolutionary: taking app development from something that could cost tens of thousands of dollars or take countless hours of manual coding, and turning it into something a motivated individual, even a child, could do in a few hours – from idea to a live, hosted prototype.
• The rapid growth of Cursor, a similar AI coding assistant, shows there's a massive appetite for these kinds of tools. I'm personally very excited about where Firebase Studio could go.

Google's Position: The New AI Leader?

• The overwhelming feeling right now is that Google is "back in town," "back on top," and has become "the ones to beat" in the AI race.
• I believe Google has more resources, a wider reach across all the necessary technologies (including their own hardware for training and running these models), and they're not as desperate for immediate AI-related revenue because their search ad business is still a cash cow. This gives them a lot of breathing room.
• The big question is whether Google's lead is now so significant that it's becoming unbeatable, and if we'll see their models consistently dominating the leaderboards.
• Get ready, because all these stealth models we've been talking about (Dragon Tail, Night Whisper, Quasar, and others) are expected to start being officially released "any week now," and they'll probably come thick and fast. As they say, it truly is "what a time to be alive" if you're interested in AI!