In the news
Adaptive Verification in vLLM: DSpark confidence-scheduled verification
vLLM · vLLM Team · Published · 3 min read
In 30 seconds
- What happened
- vLLM added adaptive verification to speculative decoding, dynamically trimming draft tokens per step based on confidence scores instead of using fixed lengths.
- Why it matters
- Matters for engineers running large language models at varying batch sizes, especially when balancing throughput and latency across different concurrency levels.
- Watch out
- Requires full varlen CUDA graph support, incompatible with eager execution, LoRA, pipeline parallelism, and output logprobs. Limited to specific attention backends.
Listen to this summary
- llm
- throughput
- latency
- token
- vllm
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