decode throughput
Decode throughput refers to the rate at which a large language model generates output tokens during the autoregressive decoding phase. It is a critical metric for evaluating real-time user experience, latency, and cost-efficiency in production environments.
Key Metrics
- Tokens per Second (TPS): The primary measure of generation speed.
- Time to First Token (TTFT): Often correlated with prefill throughput, affecting perceived responsiveness.
- Context Window Impact: Throughput typically degrades as context length increases due to attention mechanism overhead.
Recent Benchmarks & Evaluations
- Qwen 3.8-Max Performance: Evaluated for fundamental performance metrics and agentic task capabilities.
- Demonstrated excellent prefill speeds, ranging from approximately 640 tokens/second for short prompts.
- See detailed analysis: Qwen 3.8-Max Performance Benchmarks and Agentic Task Evaluation
- Full source: Qwen 3.8-Max Performance Benchmarks and Agentic Task Evaluation
Optimization Strategies
- Quantization: Using INT8 or FP8 weights to reduce memory bandwidth bottlenecks.
- Speculative Decoding: Leveraging a smaller draft model to accelerate the decoding process.
- KV Cache Management: Efficient caching to minimize redundant computation for repeated contexts.