So it's February 2026. And if you're like most
people I talk to, you're probably looking at
a credit card statement that it looks less like
a bill and more like a menu. You've got your
$20 a month for one AI, maybe another 20 for
some pro model, 15 for an image generator. And
it just, it adds up. Oh, it adds up fast. But
here's the thing. While all the big labs are,
you know, charging admission at the front door,
there's this parallel reality happening, an underground
network, so to speak, where the exact same technology
and talking models like Gemini 3 .0 Pro, Claude
Opus 4 .6 is just sitting there. Fully unlocked
for absolutely nothing. It sounds like a scam
when you say it out loud, doesn't it? Like one
of those old one weird trick pop -up ads. It
really does. But it's real. And honestly, it's
the most exciting shift I've seen in this space
all year. Yeah. We aren't just talking about
saving a few bucks. We're talking about getting
access to tools that are, in some pretty specific
ways, actually better than what you pay for.
Welcome to the Deep Dive. Today, we're going
to explore this free AI revolution. We have a
whole stack of research here on, I think, four
specific platforms that are really changing the
game right now. Yeah, four big ones. And the
mission for this conversation isn't just to give
you a list of free stuff. It's to understand
a new way of working. Because, you know, usually
when something's free online, you're the product.
Or the quality is just... Damage, yeah. So I
have to ask... Is this a deep dive into second
rate knockoffs or is this actually usable tech?
That's the skepticism I was expecting. And honestly,
it's healthy. You should be skeptical. But what
we're seeing in the research on these platforms,
Arena AI, Veer, ChatGLM, and Quinn, it's not
about knockoffs. It's about a fundamental shift
in how compute is being distributed. We're not
just talking about saving 50 bucks a month. We're
talking about something called platform matching.
Platform matching. Let's unpack that term before
we get into the tools themselves. What does that
actually mean for, say, the average user? Sure.
For the last few years, people really identified
with a brand. You were a chat GPT person or a
cloud person. Right. You paid your subscription
and you kind of forced that one model to do everything
for you. Write code, make pictures, summarize
your PDFs. Platform matching is the realization
that in 2026, there is no single God model. This
underground network lets you use the absolute
best tool for a specific job without a paywall
getting in your way. So it's moving from a generalist
approach to a specialist one. Exactly. And it's
about redundancy. If your main model hits a rate
limit or maybe refuses to answer a sensitive
question, you need a backup. This network gives
you that. It's building a workflow that doesn't
break. Okay, let's map this out then. We're going
to look at four key players today, Arena AI,
Veer, ChatGLM, and Quinn. By the time we're done,
the goal is for you to know how you could build
a full app, generate 4K video, and do deep academic
-level research. All without pulling out your
wallet. Not even once. That's the goal. So let's
start with the philosophy of it. This source
material talks about this concept of an underground
network. And it feels like, you know, in 2026,
the question just isn't, can I afford the best
AI anymore? That's not. It's, do I know where
to find it? Right. And the cornerstone of this
whole network is a platform called Arena AI.
Right. Now, you might know them from their leaderboards,
but they just raised a massive amount of money,
like $150 million to... basically democratize
access to this stuff. Wow. And they're offering
a feature that I think completely changes how
we interact with these models. It's called Battle
Mode. I love this concept, but I also find it
a little unsettling. So let's unpack Battle Mode
because usually we're biased, right? We see a
logo, we see GPT -5 or whatever, and we just
assume it's the best. Precisely. We are brand
snobs. Yeah. Total snobs. If I show you an answer
and I label it GPT -5, you are statistically
more likely to rate it higher than the exact
same answer labeled Llama Open Source. We trust
the logo. We trust the logo. Yeah. So Arena's
Battle Mode. It strips the logos away. It gamifies
the Turing test. So how does that workflow actually
work? I type in a prompt, and then what happens?
You type in, say, write a Python script to scrape
real estate data. Arena then spins up two anonymous
models side by side, Model A and Model B. They
both generate the code on your screen at the
same time. You have no idea who they are. So
you just look at the code. You look at the code,
you test it, and you vote for the winner. It
forces you to value the output. over the label
it's a blind taste test for intelligence it is
and once you pick say option a it reveals aha
that was gemini 3 flash it just removes all the
marketing fluff okay but beyond the battle arena
has a direct chat feature that's incredibly practical
you don't have to battle if you don't want to
you can just manually pick the heavy hitters
the guide mentioned using gemini 3 pro specifically
for messy documents now help me understand the
distinction here why pro what makes that different
from the standard free models you see everywhere
else that's a great question the pro designation
it usually implies a larger parameter count And
more importantly, a much larger context window.
The context window being? Basically, the AI's
short -term memory. A standard model might remember
the last 10 pages of your conversation. Gemini
3 Pro can hold a massive amount of information
in its brain all at once. So if I have a really
chaotic PDF, like a 50 -page legal contract that's
just a wall of text, I need that bigger window.
Exactly. You upload that to Gemini 3 Pro through
Arena. You ask it to extract tasks, prioritize
them with color codes, critical, high, medium,
and it does it in seconds. If you tried that
on a smaller model, it would. It would hallucinate
or just forget the first page by the time it
got to the last. Or, you know, if you need real
-time info, you can just toggle on a search -capable
model like Perplexity. I saw an example in the
notes about asking for the 10 most relevant AI
news stories from the past seven days. Right.
And because it's Perplexity running through this
interface, it's not just making updates. It's
searching the live web, finding sources, and
giving you inline citations. Again, totally free.
But the part of Arena AI that really stopped
me was the coding capability. We're not just
talking about writing a little snippet of Python
here. No. We're talking about building full web
apps. This is where it gets really interesting.
They have a split -screen builder. So you select
the model. The source recommends Cloud Opus 4
.5 syncing for this. And you just described the
app. The example they gave was something called
Task Atlas. Task Atlas. It sounds intense, but
walk me through what the user is doing. Are they
writing code? No. And that's the beautiful part.
The user didn't write a single line of code.
They went to Arena. pick the model, and just
describe their dream interface. I want a zoomable
canvas for my tasks. I want animated cards. I
want smart clustering. Make the buttons neon
green. It just builds it. In real time. Yeah.
The screen splits in half. On the left, the AI
is writing the HTML, CSS, JavaScript. On the
right, the app is actually running. You can click
the buttons, test the drag and drop. Wow. And
if you don't like the color of the buttons, you
just say, make them look more cyberpunk, and
the code just rewrites itself instantly. This
feels like it bridges that gap between a chatbot
and an actual IDE and integrated development
environment. But usually with these web -based
builders, you're trapped. You can't take the
code with you. That's the kicker. You can download
the entire project as a ZIP file. The guide even
suggests using a free host like Hostinger to
deploy it. So you go from a text prompt to a
live public URL without writing a line of code.
It moves from playing with AI... to actually
shipping a product. That is wild. It really makes
me wonder about that psychological shift we touched
on. If we're constantly in battle mode, choosing
the best output blindly, does that mean our loyalty
to these big tech companies is just dead? I think
it just democratizes quality. It forces the models
to actually be good, not just famous. If a smaller
open source model gives you a better answer,
it wins. The user doesn't care about the logo.
They care about the result. That's a great segue
to our next platform because this one seems to
be all about removing barriers. It's called Veer.
And the headline here is frictionless. Veer is
the antidote to subscription fatigue and login
fatigue. You know that feeling when you just
want to make a quick image, but you have to log
in, find your two factor code. Then you realize
you're out of credits. Yes. Veer has none of
that. No registration, no credit card, no usage
caps. That sounds surprisingly risky for them.
How are they preventing abuse? And honestly,
if it's that open, is the quality actually any
good? They're relying on the efficiency of the
open source models they run. It's all designed
for speed. The source highlights the text -to
-image quality mode. You type a frog riding a
bicycle through New York City, and boom, high
quality, no watermark, ready to go. I have to
admit, I get prompt drift sometimes. I'll start
with one idea, and then I get bogged down in
all the settings on other apps, and I lose the
spark. This sounds like it captures that initial
creative burst. That's the value proposition.
Speed. It's about getting into that flow state.
And it's not just static images. They have an
image -to -video feature. You can take an old
photo, upload it, and the AI animates it. It'll
make the character wave or the wind blow through
the trees. And there's something called the context
editor. Yeah, this is for style transfer. Imagine
you have a photo of your street, but you want
it to look like a 1980s anime or an oil painting
or some vintage film. Okay. You upload it to
the context editor, click a button. And it just
transforms the visual style while keeping the
geometry of the street exactly the same. It really
feels like Veer is designed for that creator
economy pace. It's fast, iterative. Disposable,
even. It raises an interesting point, yeah. With
no accounts and no login, it implies a shift
toward, like you said, disposable creativity.
You're not building a curated portfolio on Veer.
You're just treating creation as a stream. You
generate 50 images, grab the one that works,
and then you close the tab. It's gone. It's ephemeral.
Okay, let's pivot a bit. We've talked about coding
and creative stuff, but what about the office?
What about all the people drowning in PowerPoints
and PDFs? This brings us to ChatJLM. Right. And
we have to address the elephant in the room here.
ChatGLM is a Chinese platform. It's built by
Zippo AI. And in the past, a lot of Western users
have been skeptical of non -Western models. And
there are valid concerns about data privacy.
You probably don't want to upload state secrets
to a free web interface no matter who owns it.
Fair point. But the source calls it the office
powerhouse. Yeah. Why? What is it doing that
the U .S. models aren't? U .S. models are obsessed
with chat. ChatGLM is obsessed with deliverables.
The killer feature here is the PPT generator.
You know how much time we all waste formatting
slides? Too much. It's the bane of my existence.
With ChatGLM, you toggle on AI slides, and you
just say, create a professional quarterly review
deck for a marketing agency. It asks you a few
questions about tone and structure, and then
it generates a fully formatted PowerPoint or
PDF. Layouts, visuals, charts. It's just done.
But are they good? Usually AI slides look like
something a high schooler made in 1999. They're
surprisingly competent. They're structured correctly.
Yeah. And more importantly, they're editable.
It gets you maybe 80 % of the way there in 10
seconds. It turns a three -hour task into a 20
-minute polished job. And it handles documents,
too. Yeah. It's got an AI reading feature. You
can upload huge PDFs. We're talking 80 -plus
pages, like dense research papers. Yeah. It ingests
them and basically turns into a conversational
search engine for that specific document. So
you don't scan for keywords. No. You just ask
it, what are the conclusions about variable X
on page 40? And it pinpoints it for you. There
was one specific example in the notes that I
thought was really cool. The precision editing
on images. The blue hoodie example. Can you explain
how that works technically? Oh, I love this.
So usually if you want to change an image with
AI, say change the hoodie to blue, the AI regenerates
the whole thing. The guy's face changes. The
background shifts. It ruins the photo. Right.
It just rolls the dice again on the entire scene.
ChatGLM does object segmentation. It identifies
the pixels that are the hoodie. It masks them.
Changes only those. pixels to blue, and leave
the face and the background 100 % original. It's
surgical. So looking at ChatGLM, does this replace
the need for a separate office suite? Or is it
something else? I think of it as an intelligent
layer on top of the office suite. You might still
need PowerPoint to do the final polish, but ChatGLM
does all the heavy lifting. It automates that
tedious formatting work so you can focus on the
actual story. We're going to take a quick break,
but when we come back, we're going to look at
the heavy lifter. the tool for deep work that
might just replace the junior research analyst.
Stay with us. Welcome back. We've covered the
coder, which was Arena, the creative, Veer, and
the office assistant, ChatGLM. Now we need to
talk about the heavy lister. The source calls
this one industrial strength. We're talking about
Quinn from Alibaba. Quinn is fascinating because
it's really aiming for deep work. This is not
just for chatting. The standout feature here
is called projects. How is that different from
a normal chat history? Most AIs have a history
tab. It's about context and isolation. A chat
history is just a linear list. A project in Quen
is a dedicated workspace with its own memory
instructions. So let's say you're a freelancer.
You have client A who likes a formal tone and
British spelling. You have client B who likes
slang and emojis. That's a nightmare to keep
straight in your head. Exactly. So you create
a project for each of them. You upload the brand
guidelines and the tone of voice right into the
project settings. Now, every time you step into
the Client A project, Quinn becomes that employee.
You don't have to remind it of anything. It's
all isolated context. That's crucial for freelancers
or anyone juggling multiple roles. But the feature
that really caught my eye was deep research.
We hear that term a lot, but what does Ken actually
do that's different? There's a step change. You're
not just asking a question and getting a paragraph
back. You give it a prompt like, what are the
five best foods for longevity? And you set it
to advanced mode. It doesn't just answer you.
It goes off and conducts a 15 to 20 minute agentic
search. Wait, it takes 20 minutes. In the age
of instant gratification, that feels like a bug.
It's a feature. Think about it. If you asked
a human researcher that question, would you want
the answer in three seconds? No. No. You'd want
them to dig. So in those 20 minutes, Quinn is
performing agentic search. It's breaking your
question down into sub -questions. It's going
out to Google, Scholar, PubMed, News Archives.
It's reading dozens of papers, cross -referencing
them, throwing out the bad ones and synthesizing
the good ones. So it's doing the work of a junior
research analyst. Yes. And what it comes back
with is not a chat bubble. It's a 12 -page report
with citations, executive summaries, links to
the sources. That is incredible. But it's also
a little terrifying. If I can get a 12 -page
report on longevity in 20 minutes for free, am
I even a researcher anymore? I think your role
shifts. You stop being the hunter, the person
digging through pages of Google results, and
you become the editor. You become the verifier.
Your value isn't in finding the wrong information.
It's in synthesizing the AI's report and figuring
out if it's actually true and relevant. You move
up the value chain. From gathering to synthesizing.
Precisely. And on the complete opposite end of
the spectrum, Quinn is also doing high -end video.
This was the moment that made me go, whoa. I
mean, we've all seen AI video. But Quinn is doing
video with native audio. Audio, too. The example
in the source is so vivid, you prompt for a samurai
action sequence. Shaky camera, motion blur. Swords
clashing. Yeah. And the AI generates the video,
but also the sound of the metal striking, the
sound of arcane lightning crackling. It's multisensory.
And this is all free. Currently, yes. Unlimited
generation, no watermarks. So let's zoom out.
We've looked at Arena AI, Veer, ChatGLM, and
Quinn. It's a lot of firepower. It's massive.
And if we just recap, you've got Arena as the
decision engine using battle mode to write code
and pick the best models. You've got Veer for
that instant frictionless creativity. ChatGLM
is your corporate weapon for all those PDFs and
slides. And Quinn is for the really deep dives.
cinematic production. The big idea here seems
to be that in 2026, having a budget isn't the
competitive advantage anymore. No. The advantage
is knowledge. The advantage is strategy. It's
about redundancy. The person who relies on one
$20 subscription is fragile. If that model goes
down or gets dumber, they're stuck. The person
who knows this underground network. They're anti
-fragile. They can pivot. They can match the
platform to the task. That's a powerful place
to land. So here's our challenge to you listening.
Pick one task you usually pay for. Maybe it's
a stock image. Maybe it's summarizing a document.
And just try one of these free tools instead.
Just one. Absolutely. Go build an app on Arena.
Yeah. Generate a frog on a bike on Veer. Just
test the waters. Because the tools became free.
The strategy is now your job. Couldn't have said
it better myself. Thanks for diving in with us.
We'll catch you in the next one.