New Models
Ling-3.0-Flash
Ant Group's Ling-3.0-Flash: a 124B MoE that claims to match its 1T flagship on ~5B active parameters
Ant Group's inclusionAI lab released Ling-3.0-Flash, a 124B-parameter MoE activating only ~5.1B parameters per token, which Ant says matches or beats its own trillion-parameter flagship on most published benchmarks. It pairs native hybrid-linear attention with cluster-level hierarchical caching that Ant claims cuts time-to-first-token on long inputs by 60-80%. Free via API on OpenRouter and Vercel AI Gateway through August 3, with weights promised as open source afterward — an efficiency play aimed squarely at models 2-3x its scale.
124B / ~5.1B total / active parameters (MoE)60-80% claimed TTFT reduction on long inputs