How many views does "Diffusion Gemma: Google's First Open Diffusion Model" have?

As of Jul 22, 2026 · 14 days ago, it has reached 48.6K views.

How is "Diffusion Gemma: Google's First Open Diffusion Model" performing versus Prompt Engineering's normal?

About 4.1x — it has 48.6K views versus the roughly 11.8K Prompt Engineering typically draws at the same age, measured against the channel's own 90-day baseline.

AI & Tools desk — breakout report

Diffusion Gemma: Google's First Open Diffusion Model

Name: Diffusion Gemma: Google's First Open Diffusion Model
Uploaded: 2026-06-11T12:32:13Z
Duration: 12 min 44 s
Channel: Prompt Engineering
Description: Google’s Diffusion Gemma, its first open-weight diffusion-based language model released under Apache 2.0. I explain how diffusion decoding differs from autoregressive generation (parallel fixed-window generation that can revise earlier tokens), walk through the step mechanics (256-token patches, entropy/uncertainty…

Google just dropped their first open diffusion model and it's hitting way different than standard language models—the parallel token generation approach is changing how people think about LLM architecture.

Key facts

•4.1x Prompt Engineering's own 90-day median — this channel normally draws about 11.8K views at the same age.
•48.6K views so far, published 55 days ago.
•Category: Science & Technology · Language: en · Quality: HD
•"Breakout" is measured against this exact channel's trailing 90-day median at matching video age — not a generic niche average.

Updated 2026-07-22 16:55 UTC

Video thumbnail: Diffusion Gemma: Google's First Open Diffusion Model — Watch on YouTube ↗ · Prompt Engineering · 245K subscribers

View trajectory

Views this upload has gathered since it published, last measured about 988h in — from our own tracking.

Published Jun 11, 2026 · 55 days ago. How breakouts are measured →

From the creator

Google’s Diffusion Gemma, its first open-weight diffusion-based language model released under Apache 2.0. I explain how diffusion decoding differs from autoregressive generation (parallel fixed-window generation that can revise earlier tokens), walk through the step mechanics (256-token patches, entropy/uncertainty…

Category: Science & Technology · Language: en · Quality: HD

Topics: Knowledge · Technology

Tags: prompt engineering, Prompt Engineer, LLMs, AI, artificial Intelligence, Llama, GPT-4, fine-tuning LLMs

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