So there's this new AI image editing tool, right?
And it's just, it's blowing everything else away
in blind tests. Yeah, it's really something.
We're talking over 200 ELO points ahead on Elma
Arena. That's a massive gap. I mean, that really
grabs your attention, doesn't it? It changes
the whole game. It absolutely does. This thing,
we've been calling it Nano Banana, just kind
of internally. But the official name is Gemini
2 .5 Flash Image. It's really shifting how we
think about, you know, accurate photo editing.
Whole new benchmark. Exactly. Welcome to the
deep dive. Today, we're going to cut through
all the hype around this new Google tool. Our
mission really is to figure out why. Why is it
number one? Where's that power coming from? And,
you know, crucially, how can you use it for fixing
old photos, maybe, or even professional character
design? Yeah, we'll dig into the tech behind
it first, then walk through the basics, some
of the editing features. We need to talk about
the consistency stuff. That's huge. But also
look at where it kind of hits its limits creatively.
OK, good. And then we'll wrap up with some solid
tips, right? How to actually write prompts that
work consistently. So let's start with that score
gap. Okay, the numbers. They're pretty wild.
If you look at Ella Marina, most of the top editors,
they hover around 1 ,100 ELO. This tool, Mano
Banana, it's pushing past 1 ,300. Okay, wait.
For someone listening who doesn't follow these
leaderboards religiously, what does a 200 ELO
gap actually mean? It's a really good question.
Think about chess. If a player has a 200 ELO
advantage, they're expected to win about, what,
76 % of the time against the lower rated player?
It's a significant edge. So in these blind tests
where people are just picking which image looks
better or more accurate, this new model is just
winning, like three out of four times against
the best competitors out there. Pretty much,
yeah. Consistently, overwhelmingly chosen. That's
the advantage we need to unpack. OK, so if it's
that much better, the sources must be saying
it's not just slightly more data or better code.
It has to be something different at the core.
It is. The secret sauce is the foundation. Gemini
2 .5 Flash. That's Google's special model. And
the key thing is, it's multimodal. Multimodal.
Meaning it gets different kinds of info at once.
Words, pictures. Exactly. Words, pictures, sounds,
even video concepts. It understands them all
together. Ah, okay. Like stacking different kinds
of Lego blocks of data, maybe? That's a great
way to put it. Imagine editing a Lego build.
A normal tool might just see, I don't know, the
color of a brick. A multimodal one sees the color,
the shape, where it sits next to other bricks,
and it understands the written instructions to
the final thing. Oh, okay. So it has a deeper
context. Right. So because of that, NanoBanana
isn't just making images, it's editing them super
accurately, especially keeping all those little
details right. That's stability. That makes sense.
If the power comes from being multimodal, how
does that, like, technical thing translate into
a real benefit for someone just trying to fix
an old photo? Well, that reliability, you know?
Keeping tiny details consistent, like a specific
glint in someone's eye or the weave of fabric.
It just makes the tool feel much more trustworthy.
Right. It stops those weird, jarring changes
you sometimes see where the AI gets confused.
Exactly. It avoids that stuff. OK, so we get
the why. It's that multimodal foundation. Now,
for someone listening who's thinking, OK, I want
to try this, where do they actually go? Two main
places. For beginners, definitely Google AI Studio.
It's free. The interface is super simple, really
straightforward. You just upload your picture,
type what you want changed in the text box, be
specific, click Run, and then you can download
it. And Ella Marina is still there for the comparisons
if you want to really nerd out on the scores.
Right, for testing. But for actually making stuff,
AI Studio is the way to go. OK. But there's a
catch, right? The free use. There is, yeah. It's
limited right now. Usually like three to five
free edits before you hit a wall. So planning
your edits is really important. If you have a
ton of photos, the sources suggest maybe using
different Google accounts. But yeah, treat those
first few tries carefully. Like gold. Got it.
Okay, speaking of valuable stuff. Photo restoration.
The source has really highlighted this. Fixing
old family photos. That's a massive strength,
again, because of that detail retention. You
can give it an old, faded, scratched up black
and white photo and just ask simply, like, color
this photo naturally and fix the torn parts.
Doesn't just slap color on. It actually rebuilds
the missing bits, smooths out the damage, gets
the color balance right. And crucially, like
we said, it doesn't mess up the faces, does it?
Older tools sometimes tweak the expression or
the features when fixing damage. Right. This
one keeps those original features almost perfectly
preserved. That's huge for anyone trying to digitize
family albums or for historical stuff. Keeps
the soul of the picture. Exactly. So beyond fixing
old damage, how about just basic cleanup? Getting
rid of photobombers, that kind of thing. Yeah,
it's great at that, too, because it's precise.
You can tell it very specifically. Remove the
person in the background on the left, and it
intelligently takes them out without messing
up the rest. OK, now this is where, for me, it
gets really exciting, especially for creative
work. Advanced consistency, that's always been
the hard part for AI image tools. Oh, absolutely.
This is where that 200 ELO lead really feels
earned. It's ability to keep a person looking
like the same person across really drastic changes.
That's the magic. So you can give it one picture.
Yep, one reference photo. And then ask for huge
changes. Like put them in a totally different
outfit, a beige wool jacket, maybe then a long
green dress. Change the whole background, move
them from inside an office to like an autumn
garden. And the face. It just stays the same.
perfectly consistent through all that. Undeniably
consistent. It's uncanny. Whoa. OK, that is the
moment of wonder. Imagine how much time that
saves for, say, game designers making character
sheets. Exactly. Or concept artists. You need
consistent looks for characters, whether it's
anime or detailed robots. Just use text prompts
for the changes and the core character doesn't
drift. It's amazing. It shrinks that whole tedious
process down, right? Ensuring lighting is the
same, features are the same. from potentially
hours to just seconds of prompting. The scalability
is, yeah, it's pretty mind -blowing. And this
consistency, does it carry over into things like
virtual try -on? The sources mentioned that was
a big plus. Totally. That's another area where
it really pulls ahead of other apps right now.
OK. And we're not just talking simple stuff like
putting one shirt on one person. It handles more
complex swaps, too. Yeah. Especially in group
photos. Give me an example of a complex swap.
What does that look like? OK. Picture a photo
with, say, three or four people. You can tell
the AI. Swap the entire outfit of the man in
the blue shirt with the outfit of the woman in
the red shirt. But keep everyone else exactly
the same. And it does it. It transfers the clothes,
the style, the fit, the texture between those
two people, keeps their faces right, and doesn't
make a mess of the background. That's impressive.
OK, so if it's that good with characters and
details, where do things start to break down?
When are you pushing it too far? What's the first
sign? Usually style changes. That's where the
cracks appear first. Especially complex artistic
requests, things far away from just realism or
simple photo effects. Right. Even with that amazing
consistency, the sources mentioned this art gap,
a limit we need to be aware of. Correct. It's
great at realistic style changes. Making a photo
look like it was shot on old film, easy. Turning
it into a realistic -looking oil painting. does
that well. Adjusting mood and lighting too. Yeah,
excellent that. Warm sunset light, gloomy rainy
day effects, no problem. But the really artsy
stuff is harder. That's where it struggles. If
you say make this real photo look like true cell
shaded anime, the results. They often look more
like a detailed pencil drawing, maybe with anime
colors, but not the actual style. And mixing
styles, that's a big failure point currently.
Like our Lego analogy, asking for left half Lego
style, right half Pixar style, is usually too
much. Too confusing for it. Yeah, it's like trying
to combine incompatible instructions. Too many
style words at once. Watercolor, vintage, pop
art just leads to messy, weird results. And complex
scene changes too, like changing multiple objects
in a big way. Right, the source has had that
example. turn all the girls into cats and boys
into dogs in a group photo. That's just asking
way too much right now. Too many individual changes
at once. Yeah. I still wrestle with prompt drift
myself sometimes. You try to combine too many
things. Oh, yeah. I tried to get it to put a
tiny Viking helmet on my dog and give him a glowing
laser sword in his mouth in the same edit. Huh.
How did that turn out? It was just... A mess.
A melted, weird, inconsistent blob. It's easy
to overload it. That's actually really helpful
to hear because it shows it's not just user error
sometimes. The tool has limits. Definitely. So
if we know it struggles with those really complex
multi -part edits, what's the best strategy?
How do you get the result you want? You got to
break it down. Always. One simple change at a
time. Edit the main object first, then change
the lighting, then maybe add a simple style.
Atomic steps. OK, one step at a time. Makes sense.
So going back from the limits to the strengths
micro editing, tiny, precise changes. Yes. This
is where that Gemini flash precision really comes
through. Things like just changing eye color
or adding just a little smile, stuff that other
tools might use as an excuse to redo the whole
face. Exactly. Nano Banana handles that delicately.
And the consistency holds up so well, you can
actually generate like a grid of nine different
facial expressions. Happy, sad, angry, surprised
from one starting photo. Wow. And the person
still looks like the same person underneath with
the same features, same lighting. That's super
valuable for professional uses. How about text
and images? That's usually a nightmare for AI.
It's surprisingly decent here, though language
translation can be hit or miss. But simple replacement
works pretty well. changing a sign from welcome
home to happy birthday. It can often do that
while keeping the original font style in perspective.
It seems to treat the text like an object that
needs to preserve or change carefully. OK, so
to really leverage all this power, you need good
prompts. The sources laid out a structure, a
way to get better results, especially with those
limited free uses. Yeah, a simple three -part
structure helps you think clearly. First, the
action. What are you changing? Change the car
color to red. OK. Second, the constraint. What
needs to stay the same? Keep the background and
the driver exactly the same. Constraint. Got
it. And third, the style. What's the desired
quality or feel? Make it look like a professional
car ad. Action, constraint, style. That structure
helps avoid those accidental changes. The drift.
Exactly. It forces clarity. And since those free
turns are precious, the advice is plan your edits.
Use clear, simple language, and definitely save
prompts that work well so you can reuse them.
Smart. And always double check the output. Absolutely.
Final QC is crucial. Check the face consistency
again. Did it actually make all the changes you
asked for? Sometimes it misses one. And look
carefully near the edges of your edit. Did anything
weird happen in the background that you didn't
intend? Good checklist. So this amazing tech
is in Google AI Studio now, but the sources were
clear. This is just the flash version. Right.
That's the key point. This is the fast accessible
version, the one winning the ELO scores. But
there's likely a more powerful full version of
Gemini behind it, maybe still to come. And developers
can already tap into this? Yep. The API is available
so people can build tools that integrate this,
allow editing through, like chatting with the
AI, or combine multiple images in really sophisticated
ways. The potential is huge. OK, so let's boil
it down. The big takeaway here. I'd say it's
that NanoBanana's multimodal core gives it just
unmatched consistency, especially for tiny edits
and keeping characters the same across big changes.
Right, but the challenge, the thing users need
to remember... You have to respect its limits,
especially with complex art styles, and always,
always break down big ideas into small, simple
steps. Don't try to do everything at once. So
the call to action is... Pretty clear. Yeah.
Head over to Google AI Studio. Try some simple
edits first. Just feel that consistency. It really
does change how you think about what AI can do
with images. And maybe final thought to leave
people with, that 200 ELO gap. It suggests this
isn't just a small step forward. It feels like
a fundamental shift in defining what realistic
even means for digital images, right? It really
does. What other fields, you know, beyond photos,
architecture, product design, might get completely
reshaped by this kind of seamless, super precise
AI integration, something to think about. Definitely
something to ponder. Thank you for sharing your
sources with us today. We really hope this deep
dive was useful for you. We'll catch you on the
next one.