LLM Performance
Mis à jour le 2026-06-11Confiance : medium
performance-metricstokens-per-secondinference-speedbenchmarkingoptimization
Metrics and techniques for measuring and optimizing the operational performance of large language models, particularly focusing on inference speed and throughput.
Key Metrics
Tokens per Second
- Primary measure of generation speed
- DiffusionGemma: 500+ tokens/second
- Previous Google Gemini Diffusion: 857 tokens/second
- Critical for real-time applications
Response Latency
- Time to first token
- Total generation time for complete responses
- Important for user experience
Performance Factors
Architecture
- Diffusion-based models showing competitive speeds
- Model size vs. speed trade-offs
- Hardware optimization considerations
Infrastructure
- Cloud API hosting (NVIDIA NIM)
- GPU acceleration requirements
- Memory and compute resources
Benchmarking Context
Real-world performance testing provides practical insights beyond theoretical capabilities, as demonstrated by Simon Willison's hands-on testing of DiffusionGemma generation speeds.
See also
- diffusiongemma
- diffusion-based-language-modeling
- nvidia
- Token Generation