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Ant Ling open-sources two 6B models in the Ming-Image-0.1-Design series

Ant Ling has open-sourced the Ming-Image-0.1-Design series, comprising two 6B models: Design generates complete visual designs such as UIs, infographics, and posters from text requirements, while Layer decomposes a design image into 2–9 semantically independent RGBA layers; Design Skill and PPT Skill are also open-sourced. In the UI/UX Design evaluation updated by Artificial Analysis on September 18, 2026, Design ranks 1st among open-source models with an Elo score of 1082; Layer achieves the best results on all 12 metrics of Crello-Test, reducing single-inference time from 795 seconds to 183 seconds. After Ant's internal Huamei integrated Layer, the time to first obtain editable layers dropped from over 5 minutes to about 40 seconds.

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Ant Ling releases finance-enhanced model Ling-3.0-flash-Fin

Ant Ling releases its first finance-enhanced model, Ling-3.0-flash-Fin, which continues the Ling-3.0-flash architecture, maintaining 124B total parameters and 5.1B activated parameters. Through continued pre-training on financial corpora, domain post-training, and tool-use optimization, it strengthens the handling of complex financial content such as annual reports and financial workbooks. The model was tested on benchmarks including FinFIRST, FinSearchComp Verified, Finance Agent, APEX-Agents, SpreadsheetBench, and τ³-Banking, with its AA Intelligence Index v4.1.1 score rising from 38 to 41. The model will offer a one-month limited-time free API on OpenRouter, and its weights will be open-sourced next week.

Ant Ling Open-Sources Ling-3.0-tiny: 7.9B Total Parameters, 1.3B Activated Parameters

Ant Ling has officially open-sourced Ling-3.0-tiny, a native hybrid reasoning model with 7.9B total parameters that activates only 1.3B parameters during inference, available in BF16, FP8, and INT4 versions. The company says it scores 25 on the Artificial Analysis Intelligence Index and 16 on the Agentic Index, with output speed exceeding 160 tokens/s. The model can run FP8 inference on a single NVIDIA DGX Spark with weights of about 7.85GB, and has been adapted for local execution on Apple Silicon MacBook and Mac mini.

Ant Ling Open-Sources Ling-3.0-flash Hybrid Reasoning Model

Ant Ling has open-sourced Ling-3.0-flash, a new-generation native hybrid reasoning model built on a MoE architecture with 124B total parameters and 5.1B activated parameters, and is simultaneously releasing a base version along with multiple precision versions including FP8, FP4, and INT4. The model supports three deployment approaches: cloud API calls, end-to-end local inference on a single NVIDIA DGX Spark using the MXFP4 or INT4 version, and high-performance deployment achieving an average output rate exceeding 1100 tokens/s under designated GPU test configurations. On the Artificial Analysis leaderboard, its output speed is 353 tokens/s, and in the AA Intelligence Index, the weighted average invocation cost per task is approximately $0.04.

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