back to top
HomeTechGoogle's Gemini Omni Can Write Math on a Chalkboard. AI Video's Hardest...

Google’s Gemini Omni Can Write Math on a Chalkboard. AI Video’s Hardest Problem May Be Getting Easier

Google's Gemini Omni Can Write Math on a Chalkboard. AI Video's Hardest Problem May Be Getting Easier
Mohit Geryani
By Mohit Geryani
0
Last updated:
- Advertisement -

Google hasn’t announced Gemini Omni. A reddit user just found it anyway.

Someone opened their Gemini app, got a pop-up for a model they’d never heard of, and started generating video. What came out has been making rounds on Reddit for the past few days, mostly because of one clip.

The chalkboard video is why.

A professor writing a full mathematical proof in chalk, narrating as he goes, text legible, delivery natural, physics mostly convincing. AI video has never handled text well. This one does. And it’s not just text, the audio, the movement, the realism are all hitting at a level that has people genuinely uncomfortable in a way the usual AI video demos don’t.

It’s a leak. Google hasn’t said a word. I/O is next week. But whatever Omni is, the early results suggest something shifted.

What we know about Omni

Not a lot, officially. The user got a pop-up in the Gemini app prompting them to “create with Gemini Omni”, described as a new video generation model with the ability to remix videos, edit directly in chat, and use templates. That’s the entire official description. Google hasn’t confirmed anything exists.

Max Weinbach dug into the metadata and found that Omni appears to be an extension of Veo rather than something built from scratch. Which tracks. Google has been developing Veo for a while and the output here looks like a significant step forward from what Veo was producing, not a completely different direction.

I/O is next week. That’s almost certainly when this becomes official and we get actual details on what Omni is and how it fits into the broader Gemini lineup.

Where it still lacks

The chalkboard result is impressive. The spaghetti test is a different one.

The original Will Smith prompt got blocked by Omni’s guardrails, so the user rewrote it, two men at a seaside restaurant, white tablecloth, approaching the table and eating spaghetti while having a conversation.

Spaghetti appears from nowhere on plates that were empty seconds earlier. The eating doesn’t match the bites. The inconsistencies that the chalkboard video mostly avoids stack up quickly here. Another Reddit user ran the same prompt through ByteDance’s Seedance 2 and got a noticeably more consistent result.

So Omni isn’t uniformly ahead of everything. The text handling is genuinely new. Physical realism on complex interactions still has the rough edges you’d find elsewhere.

You May Like: daVinci-MagiHuman Finally Makes Open-Source AI Video Feel Real

The usage question most ignore

Those two generations, the chalkboard and the spaghetti consumed 86% of this user’s daily quota on a Google AI Pro plan. There was some Gemini Flash usage the same day so it’s not a perfectly clean number, but the direction is clear. Video generation on Omni is expensive in terms of quota, and that’s going to be the conversation nobody is having right now but everyone will be having the moment Google makes this official and people hit their limit inside the first two prompts.

What comes next

Google said video is here to stay after OpenAI shut down Sora earlier this year. Omni looks like the proof of that commitment. The chalkboard result alone suggests something real has shifted on the text rendering problem, even if the model isn’t consistent across all prompts yet.

We’ll know the full picture next week. Until then the chalkboard video is the thing worth watching twice.

Don’t miss any Tech Story

Subscribe To Firethering NewsLetter

You Can Unsubscribe Anytime! Read more in our privacy policy

LEAVE A REPLY

Please enter your comment!
Please enter your name here

YOU MAY ALSO LIKE
OpenAI Built Its First AI Chip. It's Not Trying to Replace NVIDIA

OpenAI Built Its First AI Chip. It’s Not Trying to Replace NVIDIA.

Mohit Geryani - 0
When the news broke that OpenAI had built a custom chip, the instinct was to frame it as a NVIDIA story. Another lab trying to cut the cord, reduce dependence on H100s, claw back some margin from the company that's been printing money off the AI boom. That's not quite what's happening here. The chip is called Jalapeño, built with Broadcom, and it doesn't touch training at all. It's an inference chip, meaning it only runs models after they're already built, when a user sends a message and ChatGPT has to respond. The compute-heavy work of actually training those models still runs on NVIDIA hardware. OpenAI isn't replacing NVIDIA. It's going after a different part of the problem entirely, the part that happens millions of times a day, every time someone uses one of their products. That distinction matters because inference is where AI costs actually accumulate at scale. Training happens once per model. Inference never stops.
glm 5.2 ai open weights

GLM-5.2 Is the Closest an Open Model Has Come to Claude

Mohit Geryani - 0
What does it take for an open-weight model to stop chasing Claude and actually beat it? Every open-weight release for two years has told some version of the same story: closer, but not quite. The chart shrinks, the wording softens to "competitive with," and the conversation moves on until the next model repeats the cycle. GLM-5.2 breaks that pattern. The model is built to survive long, messy coding work, the kind that runs for hours without losing the thread. That's the pitch its maker is leading with. But scroll down their own benchmark table and something else is sitting there quietly: on a couple of standard math evals, this open model isn't approaching Claude Opus 4.8, GPT-5.5, or Gemini 3.1 Pro. It's beating all three, on the same table. It loses plenty of ground elsewhere, and that part matters just as much as the wins. But a model anyone can download under an MIT license, with no usage restrictions attached, coming out ahead of the lab everyone else measures themselves against, is worth pausing on before getting to what the rest of the numbers actually say.
Open-Source AI Tools Worth Trying Right Now

5 Open-Source AI Tools You Probably Haven’t Tried Yet

Mohit Geryani - 0
Every week brings another open source AI release, and most of them require setting up a Python environment. Find out the model card lied about VRAM requirements. By the time something actually runs, the appeal has mostly worn off. The five tools below skip most of that. One turns image and video generation into something closer to a desktop app. One gives DeepSeek an actual workspace instead of a browser tab. One builds UI prototypes using coding agents you probably already have installed. One quietly builds a memory system out of your own apps. And one is, literally, a desktop pet.