open-weight AI
3 picks we've reviewed.
GLM-5.2
Zhipu's open-weight coding flagship: a 753B mixture-of-experts model with a 1M-token context and MIT weights, claiming to edge past GPT-5.5 on coding benchmarks.
VibeThinker-3B
A 3-billion-parameter open reasoning model that claims to match systems hundreds of times its size on math and code — and has the AI world arguing about whether the benchmarks are real.
MiniMax M3
MiniMax's third-generation flagship — M3 is an open-weight 428B-parameter MoE (~23B active per token) using MiniMax Sparse Attention (MSA), with a 1M-token context window and native multimodality (text, image, and video input). It's positioned as the first open-weight model to combine frontier coding, a 1M context, and native multimodality — and can even operate a desktop computer.