RIP Deepseek. We have a new #1 open-source AI model

RIP Deepseek. We have a new #1 open-source AI model

🎙 AI Search 👥 715K 📅 October 29, 2025 ⏱ 23 min 👁 209K 📄 expert opinion 🧭 2026-08-03
Available in: English (current) Français

Keywords

MiniMax M2open-sourceAI modelcodingagentic

Summary

The video reviews MiniMax M2, a newly released open-weights AI model that the creator claims is now the best open-source model, outperforming even some closed models like GPT-5 and Claude 4.5 in certain tasks. The host demonstrates the model’s capabilities through a series of prompts, including creating a Photoshop clone, a 3D interactive map of Tokyo, a jigsaw puzzle app, a beehive simulation, a financial analysis report on Nvidia, a CRM dashboard, and a racing game. Each demonstration shows the model’s ability to generate functional code and interactive web applications. The video also includes a segment sponsored by Gamma, an AI presentation tool. The creator highlights MiniMax M2’s strong performance on independent leaderboards, particularly in coding and agentic tasks, and discusses the importance of open weights for accessibility and fine-tuning. The video concludes with a discussion of the model’s specifications and benchmarks, emphasizing its competitive edge over other open-source models.

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Critical Evaluation

The video provides a compelling demonstration of MiniMax M2’s capabilities, showcasing its proficiency in generating complex code and interactive applications from natural language prompts. The creator’s approach is hands-on, testing the model with diverse and challenging tasks, which adds credibility to the claims. However, the evaluation is largely anecdotal and lacks rigorous scientific methodology. The creator does not provide quantitative comparisons with other models beyond referencing an independent leaderboard, and the demonstrations, while impressive, are not systematically benchmarked. The video also includes a sponsored segment for Gamma, which is clearly disclosed, but it interrupts the flow of the content. The creator’s enthusiasm is evident, but the lack of critical analysis of potential limitations, such as the model’s hallucination tendencies (briefly mentioned) and the occasional errors in outputs (e.g., the 3D buildings toggle not working), is a minor weakness. The sources cited are primarily the model’s official page and the creator’s own tools, which are relevant but not diverse. Overall, the video is informative and well-produced, but it should be viewed as an expert opinion rather than a scientific study. The title’s ‘RIP Deepseek’ is sensationalist, but the content largely supports the claim that MiniMax M2 is a top open-source model.

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Title / Content Match

The title is somewhat sensationalist ('RIP Deepseek') but accurately reflects the claim that MiniMax M2 is a new top open-source model, as demonstrated in the video.

Quality & Reliability

7/10

The video provides a hands-on review of MiniMax M2, demonstrating its capabilities through various prompts and comparing it to other models. The creator shows actual outputs and mentions independent benchmarks, but the evaluation is subjective and lacks rigorous scientific methodology. The presence of a sponsor segment is disclosed, and the creator does not claim to be sponsored by MiniMax. Overall, the information is useful but not peer-reviewed.

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Contribution & Novelties

The video provides a practical, hands-on evaluation of MiniMax M2, an open-weights AI model, demonstrating its capabilities in coding and agentic tasks. It highlights the model’s performance on independent leaderboards and its potential to rival closed models. The creator’s demonstrations offer concrete examples of the model’s utility for generating interactive web applications and data visualizations.

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Radar Profile

The radar profile shows high scores in information quantity and quality, reflecting the video's comprehensive demonstrations and accurate data. The technical level is moderate, suitable for a general audience, while reliability is good but not perfect due to the subjective nature of the review.

Reliability 7/10

💬 Très positif : les commentaires sont extrêmement favorables, louant la qualité du contenu et l'utilité des démonstrations, avec quelques remarques humoristiques et remerciements au créateur.