Finance-enhanced Ling variant
According to the model card, the model extends Ling-3.0-flash through continued training on financial data with financial institutions and domain experts.
Open Source Model Profile · inclusionAI
Ling-3.0-flash-Fin is a 127.49B-parameter finance-enhanced text-generation model from inclusionAI. Its model card documents continued training from Ling-3.0-flash for financial research.
Ling-3.0-flash-Fin is published by inclusionAI as a text-generation model. The captured configuration identifies BailingMoeV3ForCausalLM with model type bailing_hybrid, and Safetensors metadata reports 127,486,405,600 parameters. According to the model card, it is a finance-enhanced continuation of Ling-3.0-flash, with MIT recorded as the license.
According to the model card, the model extends Ling-3.0-flash through continued training on financial data with financial institutions and domain experts.
Safetensors metadata reports 127,486,405,600 parameters, while the model card describes 124B total parameters with 5.1B activated.
According to the model card, highlights include end-to-end financial research and source-grounded search with FinFIRST for transparent evaluation.
The model card documents BF16 release with SGLang and vLLM compatibility, plus thinking mode with temperature 1.0, top_p 0.95, and top_k 20.
Source: inclusionAI/Ling-3.0-flash-Fin
Captured: Unknown. Processed: 2026-09-07T19:34:47.070365+00:00.
Ling-3.0-flash-Fin Base Model | OpenRouter | Announcement Introduction Ling-3.0-flash-Fin is the first finance-enhanced model in the Ant Ling family. Developed by Ant Group with leading financial institutions and domain experts, it extends Ling-3.0-flash through continued training on high-quality financial data. With 124B total parameters, 5.1B activated parameters, and a 256K context window, the model combines financial expertise with efficient inference for long-horizon agent workflows. Highlights End-to-end financial research: connects information retrieval, evidence review, calculation, modeling, and report preparation instead o…
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