BAGEL AI Review: ByteDance's Open-Source Multimodal Beast Tested

Is BAGEL AI Worth the Hype? A Hands-On Look at ByteDance's New Model

Let’s get one thing out of the way: BAGEL AI has nothing to do with breakfast. I know, I was disappointed too. But what it does bring to the table is ByteDance’s first real stab at an open-source multimodal AI model—a big leap toward democratizing powerful AI tools. So, of course, I had to try it.

After poking around GitHub, tinkering with HuggingFace, and eventually surrendering to the paid route via F-AI, I gave BAGEL a real-world spin. Here’s how it went.

First Impressions: Not Just Another Text Bot

BAGEL isn’t just a text generator; it’s got visual superpowers. This thing can:

• Analyze and describe images
• Edit elements inside a photo
• Generate visuals from prompts
• Shift styles (yep, that’s aesthetic transfer)

On paper, it sounds like the open-source cousin of GPT-4V or Midjourney. But once I fired it up, I learned it’s still got some baby fat to burn.

Setup & Access: GitHub, HuggingFace & Paid Pain

Right now, your best bet to try BAGEL is to download the model from GitHub or explore HuggingFace. Unfortunately, as of writing, there’s no public demo running on HuggingFace. That left me with the fallback: F-AI—a pay-per-use platform where prompt runs cost cents but stack up fast.

⚠️ Pro tip: One image generation cost me 10 cents. Doesn’t sound like much… until you want to test 20 variations. 😅

🧪 Real-World Tests: Image Editing & Prompt Generation

The Good

First, I fed it a photo of a castle, removed an orange object, and added a wooden door. Then I deleted people from a staircase. It kinda worked—kinda. The door looked alright, and most of the people vanished. But it also axed a few innocent bystanders from parts of the image I didn’t touch. A little overenthusiastic there, BAGEL.

For image understanding, I dropped in a complex visual scene and asked BAGEL to describe it. The output? Surprisingly solid. Nothing too wild or inaccurate.

The Not-So-Great

Next up: a creative text-to-image prompt.

“Military girl headshot, Vietnamese jungle background, hyper-realism.”

Result? Decent but not mind-blowing. Took 44 seconds to generate. That’s a long time in prompt-land. Text on the image was garbled, and resolution was mid-tier.

Then I pushed it further: take that same generated image and:

• Turn her military uniform into a cheerleader outfit
• Add sprinkles to her hair
• Shift the background to a night jungle

Result? A beautiful mess. Technically, it did what I asked—kinda. But the outfit was glitchy, and those “sprinkles” looked more like static noise than glitter. Still, the fact that it followed instructions at all? Kinda impressive.

So What's Under the Hood?

Although the official paper suggests BAGEL may be using data similar to Dreamina, another ByteDance visual model, it feels like a beta version of something much bigger.

It’s open-source, so developers can build on top of it, but unless you’ve got the know-how to self-host or wait for someone else to integrate it into a more polished tool, you’ll be stuck with limited platforms like FAI.

Cool Tech, But Not Quite There… Yet

BAGEL AI is ambitious. It’s powerful in theory, and in the right hands (with the right hardware), it could go toe-to-toe with the likes of GPT-4V, Midjourney, or Stable Diffusion XL. But as of now?

• It’s clunky and slow through third-party platforms.
• Image quality is hit or miss.
• Editing tools work—but lack precision.

Still, there’s something undeniably exciting about seeing an open-source multimodal model with this much potential. It might not be your daily driver yet, but it’s got a bright future ahead—especially for devs looking to tinker.

If you’re a geek like me who loves testing bleeding-edge tech before the masses catch on, BAGEL’s worth a spin. Just don’t expect buttery-smooth performance or croissant-level polish.

🕹️ Stay sharp and stay curious as we dive deeper into the world of open-source AI at Land of Geek Magazine!

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