HomeAnt Group open-sources Bai Ling large model Ling-2.6-flash
Ant Group’s BaiLing team has officially open-sourced its newest large language model, Ling-2.6-flash. Alongside the standard release, multiple quantized variants—including BF16, FP8, and INT4—are now available, offering global developers greater hardware flexibility and significantly reducing the barriers to AI deployment.
Boasting 104 billion total parameters with 7.4 billion active parameters, Ling-2.6-flash is designed for high performance. Initially tested anonymously on major international benchmarks, the model underwent extensive optimization based on community feedback, particularly improving Chinese-English switching capabilities and code generation accuracy.
Major Gains in Inference Efficiency
Technically, Ling-2.6-flash features an advanced hybrid linear architecture that maximizes computational power. On standard H20 GPU setups, it achieves inference speeds of up to 340 tokens per second, delivering throughput that surpasses many industry competitors.
Beyond raw speed, the model excels in resource efficiency. Evaluations indicate that for tasks of comparable complexity, Ling-2.6-flash uses only one-tenth the tokens of similar-sized models, substantially lowering long-term operational costs for businesses.
Optimized for Intelligent Agents
Addressing the growing demand for AI agents, Ant Group has enhanced the model’s specialized capabilities. It demonstrates robust logical execution and high task success rates, whether handling complex tool calls or executing long-chain planning scenarios.
The model is now accessible on leading open-source platforms like Hugging Face and ModelScope. Through this comprehensive open-source strategy, Ant Group aims to empower developers across various industries to explore new frontiers in large-scale AI applications while maintaining strict data privacy standards.
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Ant Group’s BaiLing team has officially open-sourced its newest large language model, Ling-2.6-flash. Alongside the standard release, multiple quantized variants—including BF16, FP8, and INT4—are now available, offering global developers greater hardware flexibility and significantly reducing the barriers to AI deployment.
Boasting 104 billion total parameters with 7.4 billion active parameters, Ling-2.6-flash is designed for high performance. Initially tested anonymously on major international benchmarks, the model underwent extensive optimization based on community feedback, particularly improving Chinese-English switching capabilities and code generation accuracy.
Major Gains in Inference Efficiency
Technically, Ling-2.6-flash features an advanced hybrid linear architecture that maximizes computational power. On standard H20 GPU setups, it achieves inference speeds of up to 340 tokens per second, delivering throughput that surpasses many industry competitors.
Beyond raw speed, the model excels in resource efficiency. Evaluations indicate that for tasks of comparable complexity, Ling-2.6-flash uses only one-tenth the tokens of similar-sized models, substantially lowering long-term operational costs for businesses.
Optimized for Intelligent Agents
Addressing the growing demand for AI agents, Ant Group has enhanced the model’s specialized capabilities. It demonstrates robust logical execution and high task success rates, whether handling complex tool calls or executing long-chain planning scenarios.
The model is now accessible on leading open-source platforms like Hugging Face and ModelScope. Through this comprehensive open-source strategy, Ant Group aims to empower developers across various industries to explore new frontiers in large-scale AI applications while maintaining strict data privacy standards.
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