Ling 3.0 Flash Fin

Artificial Analysis published an independent evaluation of Ling-3.0-flash-Fin on September 16, 2026, scoring it 23 on the Artificial Analysis Intelligence Index and 24 on the Finance & Accounting Index, placing it on the Intelligence-vs-Active-Parameter Pareto Frontier. The text-only model was developed by Ant Group wi Key comparative findings: Ling-3.0-flash-Fin matches MiniMax-M2.7's Intelligence Index score of 23 while activating roughly half the active parameters (5.1B vs 10B), and ties Ling-3.0-flash-VL at 24 on the Finance & Accounting Index with higher business-knowledge accuracy (17% vs 11%) but also higher business-knowledge

Ant Group announced the open-sourcing of Ling-3.0-flash-Fin at the 2026 Inclusion·Conference on the Bund on September 10, 2026, positioning it as an open model grounded in real-world financial workflows and emphasizing utility and efficiency for complex tasks. The model was co-developed with leading financial instituti Built on a Mixture-of-Experts architecture, Ling-3.0-flash-Fin has 124 billion total parameters but activates only 5.1 billion per token, delivering the broad knowledge capacity of a large model with the low inference costs and high deployment efficiency of a compact model. Ant Group reports competitive results on benc

Ant Group announced the open-sourcing of Ling-3.0-flash-Fin at the 2026 Inclusion·Conference on the Bund on September 9, 2026, framing it as an open model grounded in real financial business needs. The press release emphasizes utility and efficiency for complex tasks in domains requiring trustworthy sources, consistent Built on a Mixture-of-Experts architecture with 124B total parameters and 5.1B active parameters per token, Ling-3.0-flash-Fin aims to deliver large-model knowledge capacity while keeping inference costs and deployment requirements compact. It targets information retrieval from authoritative sources, research reasoning

On August 28, Ant Group, together with CICC (China International Capital Corporation) and industry experts, released Ling-3.0-flash-Fin as the first finance-enhanced model from Ant's Bailing (Inclusion AI) team. It retains the Ling-3.0-flash architecture and long-context capability, preserving the 124B total / 5.1B act The article characterizes the approach as mirroring a "swap post-training, not weights" philosophy—keeping the base model and pushing it toward professional scenarios through financial continual pre-training and domain post-training. In an official demo, the model processed a Google 2026 Q2 financial spreadsheet contai

Ling 3.0 Flash Fin is a newly listed finance-domain hosted model from InclusionAI, available through OpenRouter as of August 27, 2026. The defining combination is long-context handling (262,144 tokens) paired with an explicit finance orientation, making it relevant for tasks that require reasoning across lengthy, jargo The model is positioned for financial text generation and analysis, including reviewing filings, summarizing quarterly performance narratives, comparing disclosures across periods, extracting risk factors, drafting analyst-style commentary, and answering questions over long reports, along with supporting domain-specifi

TechNode reported on August 28, 2026, that Ant Group has launched the finance-tuned Ling-3.0-flash-Fin model, retaining the Ling-3.0-flash architecture and its 124 billion total parameters and 5.1 billion active parameters. The model's weight release was scheduled for the following week, and the article is sourced via Ant Group is described as offering a one-month free API period through OpenRouter for finance professionals and developers, framing Ling-3.0-flash-Fin as a domain-specialized variant of the existing Ling-3.0-flash backbone. TechNode's launch-day coverage is light on deep architectural detail beyond confirming the param

BenchLM's tracking page lists Ling 3.0 Flash Fin as released August 28, 2026, documenting a 262K-token context window and Vercel AI Gateway availability alongside its API model ID of inclusionai/ling-3.0-flash-fin. The profile is flagged as proprietary, with 489 tracked benchmarks across the model record and 3 sourced On the decision snapshot, capability is reported as unranked with a field median of 56.2 but not yet eligible for a public rank, while API input price is logged as not published (field median $0.97) and speed is listed as not measured (field median 86.5 tok/s) with time-to-first-token similarly unmeasured. The model's

The LLM Releases catalog entry for Ling-3.0-flash-Fin records the model as open weights under the MIT license, with downloadable weights available. Architecture is documented as a Mixture-of-Experts design totaling 124 billion parameters with 5.1 billion active, a 262K-token context window, and a 33K-token maximum outp The catalog entry currently has no benchmark scores recorded, with no claimed vendor figures verified on the page. As an independently maintained technical reference, it provides a clean, conservative spec card that confirms the model's MoE parameter counts, context and output limits, and MIT-licensed open-weights stat