Ant Ling officially open-sources the Ling-3.0-flash model

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On August 7, 2026, Ant Ling officially open-sourced Ling-3.0-flash, a new-generation native hybrid reasoning model. According to the Ant Ling developer blog, the model uses a MoE architecture with 124B total parameters and 5.1B activated parameters, and is released alongside a base version as well as multiple precision versions including FP8, FP4, and INT4. There are three deployment options: cloud API calls; end-to-end local inference on a single NVIDIA DGX Spark using the MXFP4 or INT4 version; and a high-performance deployment that exceeds an average output rate of 1,100 tokens/s under the specified GPU test configuration. In terms of benchmark data, its output speed in Artificial Analysis is 353 tokens/s, and in the AA Intelligence Index its weighted average invocation cost per task is about $0.04. There are currently no subsequent development facts.

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Latest development · ReportAug 7 08:00

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

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Aug 7· 1 reports
Bailing officially open-sources the Ling-3.0-flash model
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Aug 7

08:00
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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.