Ant Group Releases Open-Weight Ling 3.1 Flash 1019 with Enhanced Agentic Capabilities
Ant Group has released Ling 3.1 Flash 1019, an open-weight successor to its reasoning model, boosting the Artificial Analysis Intelligence Index score from 41 to 44. The update delivers significant gains in agentic capabilities, scientific reasoning, and code generation, featuring a 1M token context window under an MIT license.
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Artificial Analysis (@ArtificialAnlys) · 2026-10-27 18
Ling 3.1 Flash 1019, an open weights model and successor to Ling 3.1 Flash, scores 44 on the Artificial Analysis Intelligence Index v4.3, up from 41
@AntLingAGI has released Ling 3.1 Flash 1019, an update to Ling 3.1 Flash, their reasoning model with 560B total parameters, 25B active parameters, and a 1M token context window. It scores 44 on the Artificial Analysis Intelligence Index v4.3, up from 41 from Ling 3.1 Flash. Like Ling 3.1 Flash, Ling 3.1 Flash 1019 is open weights.
Key results:
➤ Ling 3.1 Flash 1019’s agentic capabilities improve over Ling 3.1 Flash. On AA-Briefcase v1.1, Ling 3.1 Flash 1019’s Elo is 1521, up 124 points from 1397 for Ling 3.1 Flash. Its Elo on GDPval-AA v2.1 is 1653, up from 1617 for its predecessor, an increase of 36 points. On AutomationBench-AA, Ling 3.1 Flash 1019 scores 68%, a 6 point increase from Ling 3.1 Flash’s score of 62%
➤ Ling 3.1 Flash 1019’s makes gains in scientific reasoning compared to its predecessor. Ling 3.1 Flash 1019 scores 43% on Humanity’s Last Exam, a 4-point improvement from 39% for Ling 3.1 Flash. It scores 26% on CritPt, an 8-point increase from 18%.
➤ Ling 3.1 Flash 1019 uses more output tokens per task than Ling 3.1 Flash. Ling 3.1 Flash 1019 uses 145k Output Tokens per Intelligence Index Task, more than 40% higher than Ling 3.1 Flash’s per task usage of 103k output tokens
➤ At $1.49 Cost per Task, Ling 3.1 Flash 1019 is more expensive than Ling 3.1 Flash but scores higher on intelligence. This is primarily driven by the higher number of output tokens used. However, Ling 3.1 Flash 1019 is still less expensive than models such as Mistral Large 4 Preview and GLM 5.3
Additional model details:
➤ Size: 560B total parameters, 25B active
➤ Context window: 1M tokens
➤ Pricing: $0.30 per 1M input tokens and $0.90 per 1M output tokens, with cached input at $0.06 per 1M (80% discount)
➤ License: MIT
➤ Availability: Ling-3.1-flash-1019 is available as an open weights model on Hugging Face, and is accessible through InclusionAI’s first party API
