Unverified50% confidenceFactExact time
Qwen3.8-Flash-Next adopts a hybrid attention mechanism of GDN plus QSA, with a total of 125B parameters plus 51B N-gram embeddings, activating only approximately 6B parameters per token.
1
Sources
50%
Confidence
Long-term
Relevance
9/5/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedQwen3.8-Flash-Next adopts a Mixture of Experts (MoE) architecture with 125B total parameters and 6B activated parameters.76% similarUnverifiedGLM-5.3-Flash adopts a hybrid architecture of sparse attention and linear attention, and runs entirely on a domestically produced AI chip cluster.66% similarUnverified第一代Qwen起步上下文窗口为2048，通过NTK插值外推到8192，训练使用Flash Attention、AdamW优化器和BF16混合精度65% similarUnverifiedLLaMA-2 70B采用80层、64个注意力头的架构，并使用GQA（8个KV头共享64个Q头）65% similarUnverifiedGLM-5.3-Flash, from Z.ai, is a multimodal MoE model with a total of 320B (320 billion) parameters, with only 18B parameters activated at any given time.63% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/862164API
curl https://kongchang.com/api/v1/knowledge/claims/862164MCP
get_claim(id=862164)