Long Context Llm

Summary: Qwen3.8-Flash-Next in 30 Seconds Qwen3.8-Flash-Next is Alibaba’s new AI model, out in August 2026. It reads text and images and writes text back, tuned for writing code and running multi-step work on your behalf. Anyone can download the model files, live since 24 August. The license is not fully permissive though, so read it before shipping it in a product. The real story: Alibaba shipped this as a dry run for the next big release, Qwen4. The identifier inside the model files literally says qwen4_exp, as in “Qwen4 experimental”. It is 125B parameters in size, but only 6B of them run for any given word. Big-model knowledge, small-model bill. It reads about 750,000 words in one go (1M tokens), and at that length it is 8x faster than its much larger sibling. Training it cost roughly 1/9 of the 397B Qwen3.7-Plus, and it still beats that model on coding and office work. It is cheap to run: $0.16 in / $0.47 out per million tokens. The flagship in the same family costs 12x that. When Alibaba shipped Qwen3-Next, the pitch was: this is not a finished product, it is next generation’s architecture released early so the community can poke at it. That architecture then carried the whole Qwen3.5 through Qwen3.8 line. ...

Meta Launch Llama 4 (Meta AI Blog) Important Note: Meta has announced a new chapter in the history of artificial intelligence today. The Llama 4 series is surpassing its competitors with its multimodal AI capabilities and revolutionary mixture-of-experts architecture. In initial tests, it manages to outperform leading models like GPT-4o and Gemini 2.0! Llama 4: A Revolution in Multimodal AI 🚀 Meta has officially announced Llama 4 models, which will open a new chapter in the world of artificial intelligence. Llama 4 is a natively multimodal large language model family: it processes text and images in a single model and stands out especially with its mixture-of-experts (MoE) architecture. Continuing Meta’s open-weight model approach, Llama 4 represents an important step in the AI ecosystem with both its performance and accessibility. ...