Meta Closes the Open-Source Door on Frontier AI
Meta's Superintelligence Labs will ship its first flagship models under a closed license, ending the company's open-source-first strategy at the frontier tier.
Llama
GPT-4 to Self-Hosted Llama 4 Migration Guide
Switch from OpenAI's GPT-4 API to self-hosted Llama 4 with near-zero code changes, but plan carefully for hardware, EU licensing, and real context window limits.
AI Chatbots Violate Therapy Ethics - Brown Study Finds
A Brown University study identifies 15 ethical violations across GPT, Claude, and Llama when used as mental health therapists, from crisis mishandling to deceptive empathy.
Kimi K2.5 vs Llama 4 Maverick: The Open MoE Heavyweights Go Head to Head
A detailed comparison of Kimi K2.5 and Llama 4 Maverick - two open-weight MoE models with radically different takes on the size, cost, and capability trade-off.
Kimi K2.5 vs Llama 4 Scout: Benchmark King Meets Context King
Comparing Kimi K2.5 and Llama 4 Scout - Moonshot AI's benchmark-crushing trillion-parameter model versus Meta's 10-million-token context window specialist.
Llama 4 Maverick
Meta's Llama 4 Maverick packs 400B total parameters into a 128-expert MoE architecture with only 17B active per token, beating GPT-4o on Chatbot Arena while matching DeepSeek V3 on reasoning at half the active parameters.
Llama 4 Scout
Meta's Llama 4 Scout is a 109B-total, 17B-active MoE model with 16 experts and a 10M-token context window - the longest of any open-weight model - with native multimodal support for text and images.
Qwen3.5-122B-A10B vs Llama 4 Maverick: The Efficiency Gap Nobody Expected
A data-driven comparison of Alibaba's Qwen3.5-122B-A10B and Meta's Llama 4 Maverick - two open-weight MoE models with radically different approaches to parameter efficiency and benchmark performance.
Qwen3.5-35B-A3B vs Llama 4 Scout: 3B Active Parameters vs 17B - Does 5.7x More Compute Actually Win?
David vs Goliath: Qwen3.5-35B-A3B activates 3B parameters and beats Llama 4 Scout's 17B active on MMLU-Pro, GPQA, and coding benchmarks - but Scout's 10M context window and native multimodal support tell a different story.
Taalas Exits Stealth With $169 Million to Hardcode AI Models Into Silicon
Toronto startup Taalas raises $169M to build custom chips that permanently etch AI model weights into transistors, claiming 73x faster inference than Nvidia's H200 at a fraction of the power.
Llama 4 Maverick Review: Meta's Open-Weight Multimodal Contender
A comprehensive review of Meta's Llama 4 Maverick, a 400B parameter open-weight MoE model with 128 experts, 1M context, and multimodal capabilities.
