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I Tested Google Veo 3 for 4 days - 26 Failures And 1 Success

#AI Tools
2025-06-24 16:287 min read

Content Introduction

In this video, the narrator shares a firsthand experience using Google's V3, expressing disappointment at the results despite the high expectations set by impressive demos. After spending $250 and four days testing various scenarios, the narrator reveals numerous failures and frustrating outcomes, highlighting the tool’s limitations, particularly with dialogue and complex scenes. While acknowledging the hype surrounding V3, they suggest caution for potential users, mentioning that alternatives like Hedra, priced significantly lower, yielded better results for basic tasks. The narrator advises viewers to consider their options carefully before investing in V3, suggesting using simpler videos and human editors instead until the technology matures.

Key Information

  • The speaker expresses disappointment after spending $250 on Google's V3, claiming that the outcomes were largely unusable.
  • Despite initial excitement about Google V3's demos, the speaker found the actual results to be subpar, revealing a high failure rate in video generation.
  • The speaker highlights specific tests that failed, including silent videos that unintentionally included dialogue.
  • The speaker contrasts Google V3 with a much cheaper alternative, Hedra, which produced better results for much less cost.
  • After extensive testing, the speaker claims that Google V3 excels only at simple, static scenes, failing at more complex tasks such as dialogue scenes.
  • The speaker advises viewers against using Google V3 for anything but basic B-roll footage and recommends waiting for more mature AI services.
  • The speaker urges people to save their money and sanity by either using their cameras for content creation or hiring real video editors.

Timeline Analysis

Content Keywords

Google's V3

A commentary on the disappointing performance of Google's V3, discussing a user's $250 investment that resulted in unusable content across 26 videos, while exposing the gap between the impressive demos and the actual outcomes. The speaker emphasizes the failures experienced with V3, including choppy videos and incorrect transformations.

AI Video Editing

Critiques the current state of AI video editing technology, particularly Google's V3. Highlights the struggles with complex scenes, dialogue accuracy, and the overall return on investment, suggesting that real human editors might be more effective and cost-efficient.

AI Tools Comparison

Compares AI tools like V3 to cheaper alternatives such as Hedra, showcasing how low-cost tools can produce better results. Encourages viewers to consider simple B-roll footage and wait for the development of more mature services, while cautioning against investing in unproven technology.

Content Creation

Discusses the implications of using AI for content creation, highlighting the importance of using realistic and feasible tools rather than overly complex and expensive models, to ensure productive and high-quality output.

Related questions&answers

What is the main issue mentioned about Google's V3?

The main issue is that the speaker wasted $250 on it and found that out of 26 videos, only one was barely usable.

What results did the speaker get from testing Google's V3?

The speaker experienced mostly failures, with only one video being usable out of 26 attempts.

What does the speaker suggest you should do instead of using V3?

The speaker suggests waiting for more mature services to be released, as well as not using V3 for complex scenes or dialogue.

Is there any good result mentioned from using V3?

No, the speaker highlights that V3 is unable to handle dialogues and complex scenes effectively, implying that the results are not worth the cost.

What alternative does the speaker provide for making videos?

The speaker suggests using a smartphone's camera for creating videos, stating that it could yield better footage in a shorter time.

How does the speaker feel after testing V3?

The speaker feels disappointed and indicates that the tool rushed an unfinished product to market and is not yet effective.

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