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GLM 5.2: O Novo Rei do Open Source e Seu Impacto no Serviço Público
Nos últimos anos, a evolução das tecnologias de inteligência artificial (IA) tem revolucionado diversos setores, incluindo o serviço público. O lançamento do GLM 5.2 tem gerado discussões acaloradas sobre sua superioridade em relação a modelos como GPT-5.5 e Opus 4.8. Essa nova ferramenta, totalmente open source, não apenas promete aumentar a eficiência, mas também oferece oportunidades para melhorar a transparência e a prestação de serviços à sociedade.
Uma das principais vantagens do GLM 5.2 é sua acessibilidade. Como um modelo de código aberto, ele permite que órgãos públicos implementem soluções personalizadas, adaptadas às necessidades específicas de suas comunidades. Isso pode resultar em atendimentos mais rápidos e precisos, além de fomentar a inovação dentro das instituições públicas. Ao explorar como ferramentas como essa podem ser aplicadas, é pertinente considerar como elas podem ser integradas nas plataformas de atendimento ao cidadão, nas análises de dados para políticas públicas e até mesmo na capacitação de servidores.
Além disso, a utilização do GLM 5.2 pode inspirar reflexões sobre como os dados são utilizados no serviço público. Com a capacidade de analisar grandes volumes de informações, essa ferramenta oferece a chance de aprimorar decisões informadas que impactam diretamente a vida da população. Contudo, é crucial ponderar sobre aspectos éticos e de privacidade no uso dessas tecnologias, para garantir que o foco permaneça no benefício coletivo.
Em suma, o GLM 5.2 representa um marco no universo open source e apresenta um potencial inexplorado para transformar o serviço público. Ao refletir sobre essa nova abordagem, é fundamental que gestores e servidores pensem em como adotar essas inovações de maneira consciente e responsável, buscando sempre melhores resultados para a sociedade. O futuro do serviço público pode, de fato, ser mais eficaz e transparente com a adoção de tecnologias como essa.
Aprenda tudo sobre automações do n8n, typebot, google workspace, IA, chatGPT entre outras ferramentas indispensáeis no momento atual para aumentar a sua produtividade e eficiência.
Vamos juntos dominar o espaço dos novos profissionais do futuro!!!
#GLM #Opensource #KING #BEATING #GPT5.5 #Opus #Fully #Tested
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No, tried the coding plan for one week. Overrated as usual. In fact, it lost its biggest selling point which was good value of money. I don't think many people would need a model which delivers 60% – 70% of GPT does with similar price but offers 3-5 more tokens with very slow speed (still)
I cancelled my sub after their jacked up rates and lower their limits. I won't be returning back to them.
About 3rd OOP class intelligence, aka 10th grade
GLM-5.2's hallucinations are really bad. The model may be good at programming, but it's useless for conversations.
It even claimed to me that it was Gemini.
For epistemic discussions, the model is completely useless to me.
Could you please add automatic Turkish subtitles to your videos?
Boss, I'm excited
GPT-5.6 Pro LEAKED & Is Coming Soon! Mythos 5 Level!: https://youtu.be/G3KfRWUj6Wc
Nice breakdown — one AI productivity move I use is asking the model to rank tasks by impact before it starts writing anything, so you don’t
It's not better than GPT or Opus; but it's close enough that the difference doesn't matter, and you'd prefer to use multiple models to review each other anyway, so it's good to have a new peer, even though it is slower
I really wish it had vision support.
I disagree, the models are capable but using double the tokens, even on simple tasks is a major drawback
Let's be real – GLM 5.2 is not very good. It's good at coding but that's it. It's a hammer; not a multitool.
Imagine that, WorldofAI doesn't have the "Ask" gemini button…
GLM-5.2 is amazing!
Praise around GLM-5.2 often misses the point. Not about matching GPT-5.5 on SWE-bench. About predicting its behavior in novel deployments. Robustness is paramount.
absolute beast, open source is officially frontier, really enjoying this alongside gpt 5.5 on codex
It's phenomenal, only thing I've noticed is that it cannot "surgically" edit the code it creates. It just rewrites the entire code. If they fixed that then it's nothing but game. GLM-5.2 for the WIN.
Can you tell me more about the Discord channel?
I keep getting rate limited trying to use it in openclaw
A new report, with a source in South Korea, suggests that the US government was uncomfortable with Mythos access to a South Korean company with alleged ties to China. The Amazon paper increased their unease. The article said the issues are still unresolved, implying that Fable won't return in a week. Since ChatGPT is also tied up in this, it could be mean further delays for 5.6 as well. The company was SK Telecom which was a member of Project Glasswing.
Z-Code is VERY cool with 5 million tokens free per day and it works with any API model with remote mobile features!
Better than 4.6 yes… but it was meh and could t beat 4.8 in a variety of real world work. It made a massive mistake early on in a SSH VPS scenario… so meh
I used it to build a test project.
It worked the way a professional web developer would do. Especially with patterns and file structure.
Whereas, I used Gemini 3.5 flash that costs 2 times as much. It delivered a pretty result, but the code was a joke. No self respecting developer would do it the way Gemini did it.
I recognized, that on first result. Gemini 3.5 flash delivered more features, when they were not requested. GLM5.2 however, delivered the requirements with well structured and coded project.
I think what Gemini 3.5 flash was doing what would be considered benchmaxing. It was trying to impress on the surface. This comes however at the cost of code quality, because Gemini was squeezing so much in the output token limit of the first shot.
I use Gemini family, because to iterate on large projects, Claude and GPT are just too expensive for any serious work. While Deepseek is just not there in terms of web development.
What I plan to do going forward is scaffold and kick of the project with core functionality using GLM5.2, then use MIMO2.5 or KIMIK2.7 Code for the next iterations. This works here, but not with Gemini because the code GLM produces is so clean and organized, it becomes a piece of cake for less powerful models to iterate on it.