u/Intelligent-Taste-36

I was practically beaten up for questioning this a few weeks ago on a Reddit subreddit.

Weeks have passed and there has been no launch. Is there any news? Is there any forecast?

I personally prefer to support companies that have open models.

And the paid use of Qwen products, for me, is linked to the decision the company will make on whether or not to launch the 3.7 open-weights version.

Hello everyone, how are you? How is the Ollama plan going for $20 and $100 in July 2026?

The implementation they did with GLM 5.2 turned out well and faster (as promised).

What are the usage limits?

Boa noite galera, tudo bem com vocês ?

Como está a fiscalização de produtos via redirecionador ?

Estão todas as mercadorias sendo fiscalizadas por Raio X ?

Importar está cada vez mais difícil neste país de ladrões de impostos. Concordam !

Colegas desenvolvedores e arquitetos de sistemas, preciso compartilhar uma enorme frustração e um alerta para que vocês não desperdicem seu tempo e dinheiro como eu desperdicei.

Caí na armadilha do Minimax 2.7 e agora caí na armadilha do M3. Deixe-me ser absolutamente claro: o Minimax M3 é terrível. Se você estiver construindo algo além de um script simples, como mecanismos ERP proprietários, soluções de dados para varejo ou qualquer coisa que exija raciocínio lógico sério, este modelo irá desmoronar em suas mãos.

Ele é completamente incapaz de manter o contexto em um ambiente de desenvolvimento do mundo real. Quando você o alimenta com um ADR (Registro de Decisão de Arquitetura) bem documentado baseado em grafos, ele fica completamente confuso. Ele alucina conexões, perde o controle das restrições e quebra a lógica arquitetural.

Pior ainda, ele falha completamente em respeitar o arquivo AGENTS.md. Definimos documentação, regras e limites claros nesse arquivo Markdown diretamente no repositório, e o Minimax simplesmente ignora tudo. Ele age como se a documentação não existisse, o que torna impossível confiar nele para uma integração séria com a base de código.

Comparar o Minimax com o Claude Opus é uma piada completa. Ele nem chega perto das capacidades do Claude Sonnet, nem alcança o Kimi 2.7. É um produto de brinquedo disfarçado por um marketing pesado para enganar os consumidores.

No meu fluxo de trabalho diário, sempre que o Minimax causa uma bagunça estrutural, aqueles que realmente se esforçam para limpar e terminar o trabalho com absoluto profissionalismo são o **Qwen 3.7 Plus** e o **Kimi 2.7**. Esses modelos realmente leem a documentação, entendem arquiteturas complexas, têm resiliência contextual genuína e levam as instruções sistêmicas a sério.

Considere isso um anúncio de utilidade pública: eu mordi a isca para que você nunca precise. Se você estiver gerenciando projetos grandes e complexos, fique bem longe do Minimax. Não se deixe enganar pelos benchmarks sintéticos, pois, na prática, ele é um desastre completo.

Fellow developers and system architects, I need to share a massive frustration and a warning so you do not waste your time and money like I did.

I fell for the Minimax 2.7 trap, and now I have fallen for the M3 trap. Let me be absolutely clear: Minimax M3 is terrible. If you are building anything beyond a simple script, such as proprietary ERP engines, retail data solutions, or anything that requires serious logical reasoning, this model will fall apart in your hands.

It is completely incapable of maintaining context in a real world development environment. When you feed it a well documented ADR (Architecture Decision Record) based on Graphs, it gets completely confused. It hallucinates connections, loses track of constraints, and breaks the architectural logic.

Worse yet, it completely fails to respect the AGENTS.md file. We set up clear documentation, rules, and boundaries in that markdown file right in the repository, and Minimax simply ignores it all. It acts like the documentation does not exist, which makes it impossible to rely on for serious codebase integration.

Comparing Minimax to Claude Opus is an absolute joke. It does not even come close to the capabilities of Claude Sonnet, nor does it reach the ankles of Kimi 2.7. It is a toy product disguised by heavy marketing to fool consumers.

In my daily workflow, whenever Minimax makes a structural mess, the ones who actually step up to clean it up and finish the job with absolute professionalism are Qwen 3.7 Plus and Kimi 2.7. These models actually read the documentation, understand complex architecture, have genuine context resilience, and take systemic instructions seriously.

Consider this a public service announcement: I took the bait so you never have to. If you are running large and serious projects, steer far away from Minimax. Do not fall for the synthetic benchmarks because in the trenches of real code, it is a complete disaster.

However, when using the 3.7 plus I was impressed with its coding efficiency. The model is good! To win my complete approval, all that's missing is for Qwen to release the 3.7 open weights.

Do you know where I can sign up to use the Qwen 3.7 Max at a better price?I don't want the Qwen Token Plan or the Qoder because in this case it's even cheaper to subscribe to GPT Pro.

If anyone knows of any good options, I would be grateful.

Hello everyone.

How are you all? I hope you are all well.

What are the usage limits on this plan? Are they more comfortable than those of GPT 5.5, for example?

Thanks

It seems that Qwen is no longer interested in open-weight models. Am I right?

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Google seems to want to invest in this. Are there any other companies that are going to release models that are open weights for home use?

There are refurbished servers with 8x V100 cores at attractive prices. Does anyone here own one? Or has anyone used one before?

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It's interesting because it's an Nvidia card and has a lot of memory.

Even with flawless Graphs, ADRs, and AGENTs.md files, GPT 5.5 today destroyed several modules of a system. Note that it chose to use \`git ignore\` in some of the files it destroyed.

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This model used to be good! That's not the case today!

Hello everyone, how are you? First of all, I ask for your patience with my question because I haven't seen the Strix Halo in action up close, and so I have many doubts.

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Is it worth buying? Does the bus speed provide a good experience for running models?

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Thank you all for being here.

In addition to Kimi drastically increasing fuel consumption when switching from the 2.6 to the 2.7, the model is no longer following larger, phased plans.

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It's creating phases on its own and doing things differently than requested. In other words, we pay more and receive something that is flawed?

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It's astonishing how eager they are to squeeze more money out of subscribers by delivering something that isn't good.

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Just as a reference for the sycophants out there, the Qwen 3.7 Max delivered the exact same plan, and did it quickly.

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For these reasons, new model ranking charts are being released, placing the Kimi 2.7 in 19th position.

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Congratulations to Monshot, which is only thinking about making more money and delivering less.

There wasn't even an explanation, Just a single word regarding the increased consumption even with the promise that the model will consume fewer Tokens for the same tasks.

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Before some wise people say that Kimi charges per request and not per token, understand that internally everything is measured in... Tokens...

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This is so true that in the K2.7 announcement they themselves cited the lower token consumption of the K2.7 model compared to the K2.6 as an advantage.

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But anyway... What I'm criticizing is the lack of transparency and the lack of respect for customers by not speaking out.

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I unfortunately signed up for an annual plan... I loved the plan and Kimi... But now it's really hard to use and not consume the entire plan.

A ) The infrastructure problems, which will be resolved.

B ) There are problems with the model, and they will be resolved.

C ) Pure greed on Monshot's part, wanting to be as greedy as the two biggest players in the market?

Yes friends... Kimi K2.7 is great! However, the $39 plan is insanely expensive! 12% of the weekly limit in 3 hours of work?????

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With the Kimi 2.6, I managed to maintain an average spending of 14% of the weekly limits per day.

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It's time to build your own infrastructure...

The company Monshot could at least keep the previous model as an option for those who don't want to spend more Tokens on their development.

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I say this because the K2.7 is clearly more powerful than the K2.6. However, it consumes MANY more tokens.

Have a great day (or night, depending on where you are).

Someone bought this Video Card?

I’ve been eyeing the Huawei Atlas 300I Duo 96GB lately. The price per gigabyte of VRAM is insane, and it looks like an amazing budget homelab option for experimenting with multi-LLM architectures or loading larger models. However, I’ve been researching the software side, and the compatibility limitations with mainstream tools (like Ollama, LM Studio, etc.) are pretty obvious due to the proprietary CANN architecture. I've been reading about the workarounds that are supposed to work, like GPUStack or running llama.cpp with the CANN backend, but I haven't tested anything myself yet.

The main headache I’m trying to understand through my research is GGUF support. From what I’ve read, running GGUFs through CANN is still super unstable and highly prone to breaking depending on the quantization method. It feels like a massive bottleneck for a card with this much memory, especially since you also have to deal with splitting models across its dual-chip setup.

Does anyone here have hands-on experience with this specific card? Also, I’d love to know if anyone has heard of any future roadmaps for better GGUF stability, or if there are alternative quantized formats that actually play nice with Huawei’s ecosystem without throwing constant errors.

Hello, I hope everyone is doing well. I'd like to consult with someone who has experience using Kokoro locally, because using the Open Router version, I'm not getting good results in languages other than English.

Do you have any tips on this? I want to train Kokoro in Brazilian Portuguese so that he speaks more naturally.

I appreciate any tips.

Thanks.