LLMPerf¶
What it is¶
LLMPerf is a tool for benchmarking the performance and cost of LLM APIs. It provides standardized tests for measuring throughput, latency, and cost across different providers and models.
What problem it solves¶
Enables objective comparison of LLM API providers on operational metrics (speed, cost, reliability) rather than just model quality, helping inform deployment and provider selection decisions.
Where it fits in the stack¶
Benchmarking. Used to measure and compare the operational performance of LLM inference endpoints.
Typical use cases¶
- Comparing throughput and latency across different LLM API providers
- Measuring cost-per-token for different models and providers
- Establishing performance baselines before and after infrastructure changes
Strengths¶
- Standardized testing methodology for fair provider comparison
- Measures practical operational metrics (latency, throughput, cost)
- Open source and extensible
Limitations¶
- Focused on API-based providers; local inference requires different tooling
- Results vary based on network conditions and API load
- Does not measure model quality, only serving performance
When to use it¶
- When selecting between LLM API providers based on performance and cost
- When monitoring API performance over time
When not to use it¶
- When benchmarking local model inference (use Ollama Benchmark instead)
- When evaluating model quality or accuracy
Related tools / concepts¶
Sources / references¶
Contribution Metadata¶
- Last reviewed: 2026-02-26
- Confidence: medium