新闻
Adaptive Verification in vLLM: DSpark confidence-scheduled verification
vLLM · vLLM Team · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- vLLM added adaptive verification to speculative decoding, dynamically trimming draft tokens per step based on confidence scores instead of using fixed lengths.
- 为何重要
- Matters for engineers running large language models at varying batch sizes, especially when balancing throughput and latency across different concurrency levels.
- 注意
- Requires full varlen CUDA graph support, incompatible with eager execution, LoRA, pipeline parallelism, and output logprobs. Limited to specific attention backends.
收听本摘要
- llm
- throughput
- latency
- token
- vllm
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