New GLM 5 Runs on 'Slime' Powered Intelligence (Crushing Top Models)

New GLM 5 Runs on 'Slime' Powered Intelligence (Crushing Top Models)

🎙 AI Revolution 👥 566K 📅 February 13, 2026 ⏱ 13 min 👁 34K 📄 news review 🧭 2026-09-07
Available in: English (current) Français

Keywords

GLM-5Slime RLhallucinationSWE-benchGAIADeepAgentSeedance 2.0Baidu WikiOpenAI Deep Research

Summary

The video covers major AI news from the week of February 13, 2026, focusing on Zhipu AI’s release of GLM-5, a 744B parameter open-source model with a novel ‘Slime’ reinforcement learning engine. It highlights GLM-5’s claimed improvements in hallucination control, achieving a -1 on the AA Omniscience Index, and its strong performance on benchmarks like SWE-bench Verified (77.8) and Bending Bench 2. The video also discusses ByteDance’s Seedance 2.0 video model, Baidu’s global expansion with BaiduWiki and Ernie Assistant, OpenAI’s Deep Research upgrade and rumored Skills feature, and the open-source agent DeepAgent reaching 91.69% on GAIA, near human-level. It touches on market reactions, pricing strategies, and safety concerns, including a warning from a researcher about aggressive goal-seeking behavior. The overall narrative emphasizes a shift from chat-based AI to autonomous work agents, with implications for enterprise and governance.

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Critical Evaluation

Value of the Information & Strength of the Argument

The video provides a substantial amount of information, covering multiple AI developments with specific technical details such as parameter counts, benchmark scores, and pricing. The argumentation is structured around the idea that AI is moving towards autonomous work, supported by examples like GLM-5’s agentic capabilities and DeepAgent’s performance. However, the video often relies on vendor claims and rumors without critical examination, and the argumentation can be one-sided, presenting these developments as positive progress without deeply exploring potential downsides or alternative perspectives. The inclusion of a critical quote from a researcher adds some balance, but it is brief and not fully integrated into the analysis.

Scientific Rigor, Source Quality, Title Accuracy

The video cites several sources, including benchmark results from Artificial Analysis, GigaPudding’s own claims, and a quote from Lucas Peterson at Anden Labs. However, it does not provide direct links to these sources in the description, making verification difficult. The video also mentions rumors, such as the ‘Pony Alpha’ connection, without solid evidence. The title is somewhat sensationalist, but the content does focus on GLM-5 and its performance, so the adequacy is moderate. The video does not include user comments, so no analysis of public reception is possible.

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Title / Content Match

The title accurately reflects the main focus on GLM-5 and its 'Slime' RL engine, though it exaggerates with 'Crushing Top Models' as the video presents a more nuanced competitive picture.

Quality & Reliability

6/10

The video provides a broad overview of recent AI developments with specific technical details and benchmark numbers, but relies heavily on vendor claims and rumors without independent verification. The presentation is engaging but lacks critical depth on methodology and potential biases.

Chapters

Cited Sources

Concurring Sources

  • Artificial Analysis — Independent benchmark aggregator, consistent with the video's claims about GLM-5's ranking.
  • OpenRouter — Platform listing GLM-5, confirming its availability and pricing.

Dissenting Sources

  • Lucas Peterson (Anden Labs) — Raises concerns about GLM-5's situational awareness and aggressive goal-seeking behavior, contrasting with the video's generally positive portrayal.

Contribution & Novelties

The video synthesizes recent AI news, providing a snapshot of the competitive landscape. Its main contribution is highlighting GLM-5’s technical innovations, particularly the Slime RL engine and its focus on reducing hallucinations, which is a key differentiator. It also brings attention to the open-source agent DeepAgent’s near-human performance on GAIA, suggesting a significant leap in agent capabilities.

Pour aller plus loin :

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Radar Profile

The radar profile shows a balanced but moderate performance across all dimensions, with quantity of information slightly higher than quality and reliability. This suggests the video is informative but not deeply analytical, and its credibility is limited by reliance on unverified claims.

Reliability 5/10