WeChat AI's 617B MoE model with 23B active parameters, demonstrating the first sequence-length scaling at frontier scale via Hidden Decoding, powering WeChat's Xiaowei assistant.

Open-source 230B parameter MoE model optimized for multi-language coding, agentic workflows, and real-world development tasks with 74% SWE-bench performance.

NVIDIA's efficient open-weight 30B MoE hybrid model with 3B active parameters, 1M-token context, and single-GPU deployment for local reasoning and coding.

Previous WizardLM-2 8x22B snapshot. Rechecked: not Microsoft's 2026 default. Drop leftover most-advanced / SoTA open crown.

Previous DeepSeek V3 snapshot. Rechecked: live path is V4 Flash/Pro. Not a GPT-4o / Claude 3.5 census.

DeepSeek V4 represents the next generation of DeepSeek's flagship AI models, building upon the success of V3 with enhanced capabilities in reasoning, multimodal understanding, and agent-based interactions.

Google DeepMind's open-weight 25.2B MoE model with 3.8B active parameters, 256K context, multimodal input, and a commercially permissive Apache 2.0 license.

Kwaipilot's open-weight agentic coding model: 35B MoE, 3B active per token, Qwen3.6 base, Apache 2.0, 262K context, top PinchBench tool-use score.

Poolside's open-weight 118B MoE coding model with 8B active parameters, a 1M-token context window, native interleaved reasoning, and an OpenMDW-1.1 license.