Alibaba’s Qwen3.7-Max: Analyzing the 1M Token Context Window
A critical look at the Qwen3.7-Max reasoning agent, exploring the trade-offs between its massive context window and local deployment feasibility.
Models
Weights, releases, and the race to scale
27 articles in this section.
A critical look at the Qwen3.7-Max reasoning agent, exploring the trade-offs between its massive context window and local deployment feasibility.
The shift toward world models marks a transition from linguistic competence to environmental competence, aiming to solve AI hallucinations through grounded reality.
Apple went all-in on on-device AI with the iPhone 15, and it’s the most sensible approach they’ve taken to the technology — because it turns out the only thing that makes sense for AI right now is not doing it in the cloud. While everyone else was building larger models and bigge
DeepSeek just dropped R1, and it shattered more than just benchmarks – it shattered pricing models. A model that matches GPT-4 Turbo on most tasks, costs 98.5% less to train, and releases its weights under a permissive MIT license. For an industry that has been charging $30 per m
DeepSeek Open-Model Disruption Breaks AI Pricing
OpenAI dropped GPT-5 last week. Google dropped Gemini 2.5 shortly after. The internet decided to pick sides. Let us talk about what actually matters. On paper, GPT-5 looks better. Benchmarks are up. Context windows are wider. Coding performance is genuinely impressive. But benchm
OpenAI has released its latest large language model, GPT-5, marking the latest iteration in the company’s ongoing series of AI model releases. The new model represents the result of several years of research and development by the company and its contributors, featuring significa