Hello everyone, how are you? I hope you are all well.
We already know that free trials end quickly and are only meant to prove the model's capabilities.
Where can we sign up for Qwen for development use?
The AI coding plan is practically impossible to subscribe to (and I'm referring to the $50 plan).
Any option (that isn't extremely slow and has a reasonable cost) ?
I found information on LinkedIn today about the Qwen 3.7 Max preview. I haven't tested the 3.6 preview, but the 3.6 Plus version, while I was programming, is simply excellent!
I got along very well with Qwen 3.6 Plus.
Version 3.7 Plus is also being released.
Is anyone else satisfied with Alibaba's templates?
I use well-organized ADRs and well-defined test plans. I use the Obsidian methodology, but even so, Minimax delivers an incomplete solution with mocks Instead of real functionalities.
Is this normal, or am I doing something wrong?
Is there a clear limit on tokens or requests in this plan? I was subscribed to the $30 plan, but my automatic renewal was turned off, and because of that, I was surprised by the price increase...
( 72 dollars ).
Hello everyone! I hope you are all well!
Do you have any news about what's happening with this plan?
Every day they tell you to come back the next day to make the purchase, and they're not actually releasing the sale.
Has this plan ended? Is there any way to subscribe to Qwen 3.6 Plus or 3.6 Max preview with a minimum quality (TPS) for a fair subscription price?
Eu tenho monitorado de perto o lançamento do Kimi k2.6, e precisamos conversar sobre um padrão perturbador e repetível. Isso aconteceu com o k2.5, e está acontecendo novamente agora.
O modelo foi lançado há cerca de 15 dias. Nos primeiros 12 dias, o desempenho estava "maravilhoso"—rápido, com alta capacidade de raciocínio e excelente seguimento de instruções. Mas como um relógio, há 3 dias, a qualidade e a velocidade despencaram.
Estou vendo uma redução estimada de 40% no desempenho geral. Ficou lento, está faltando lógica simples e parece "paralisado" comparado à versão que eu estava usando apenas na semana passada.
Minha Teoria: Roteamento Stealth para Modelos de Alto Nível
É possível que durante os primeiros ~15 dias (a "janela de euforia"), a Moonshot redirecione o tráfego para um modelo de primeiro nível (como GPT-5.4 ou Claude Sonet 3.6) para dominar benchmarks e o burburinho nas redes sociais? Então, uma vez que o período de "prévia" se estabiliza, eles ligam o interruptor e nos redirecionam para sua arquitetura nativa real—que claramente não está no mesmo nível.
Isso não é apenas carga no servidor; parece um modelo completamente diferente.
Alguém mais experimentou essa enorme degradação nas últimas 72 horas? Seus logs mudaram, ou vocês estão vendo "impressões digitais de alucinação" de outros provedores agora que não estavam presentes no Dia 1?
Precisamos expor essa estratégia de "armadilha de mel".
I’ve been testing Moonshot’s latest releases closely, and I’ve noticed a frustrating pattern. The preview performance is always "wonderful"—fast, coherent, and highly capable. However, after the initial launch phase, the model's output quality seems to degrade significantly (roughly 40% in my subjective tests and specific workflows).
It doesn't feel like the same architecture anymore. I have a few theories, but I'd love to hear yours:
Silent Quantization: Are they aggressively quantizing the model post-launch to manage the sudden influx of traffic and lower inference costs?
RLHF "Lobotomy": Are safety layers and alignment updates nerfing the model’s reasoning capabilities shortly after the hype dies down?
The "Benchmark Trick": Could they be over-optimizing for common test sets during the preview, which then fails to hold up in real-world complex tasks over time?
The difference is too noticeable to be a placebo. If the preview is just a "honeypot" that doesn't represent the long-term product, we need to start calling it out.
Anyone else seeing a drop in logic and coding ability after the first 14 days?