腾讯开源 AngelSpec 框架：破解大模型真实推理效率难题

The DFly architecture significantly improves performance, achieving the highest average throughput in tests with concurrent requests ranging from 4 to 64, thus providing robust support for efficient model deployment.

Key Points

• AngelSpec framework enhances inference throughput for large models.
• DFly architecture optimizes feature utilization and block dependency modeling.
• Achieved significant throughput improvements over traditional autoregressive decoding.
• Dynamic validation adjusts verification depth based on online load and hardware.
• Open-source project available on GitHub for community use.