---
license: cc-by-4.0
language:
  - en
tags:
  - llm
  - latency
  - benchmark
  - inference
  - observability
  - api-monitoring
pretty_name: "LLM Latency Tracker: latency and uptime for AI inference APIs"
size_categories:
  - 1K<n<10K
configs:
  - config_name: daily_aggregates
    data_files: daily_aggregates.csv
    default: true
---

# LLM Latency Tracker

Independent, continuously measured **latency and availability for AI inference API
providers**, aggregated by day. Covers **45 providers** across
**4 regions** (ap-tokyo, eu-hetzner, sa-east, us-central), built from
**1,347,917 raw probes** collected between 2026-07-23 and
2026-08-18.

Live rankings and full methodology: **[llmlatency.dev](https://llmlatency.dev)**

## How the numbers are produced

Probes run every five minutes from separate network locations and are never routed
through a gateway or an aggregator, so the numbers describe the providers themselves
rather than a proxy in front of them.

- **Network probe** — DNS → TCP → TLS → time to first byte (`ttfb`).
- **Inference probe** — time to first token on a real completion request (`ttft`).

These are different quantities, an order of magnitude apart, and they are never mixed in
one ranking. Percentiles are nearest-rank, identical to the ones shown on the site.

## Files

| file | contents |
|---|---|
| `daily_aggregates.csv` | one row per date × provider × region × probe type, with p50/p95, sample count and success rate |
| `rankings.json` | machine-readable snapshot published live at llmlatency.dev |

## Usage

```python
from datasets import load_dataset

ds = load_dataset("llmlatency/llm-latency-tracker", split="train")
ds.filter(lambda r: r["region"] == "eu-hetzner" and r["probe_type"] == "network")
```

Or without this dataset at all — there is a client on PyPI:

```bash
pip install llmlatency
llmlatency fastest
```

## Limitations, stated up front

Vantage points are cloud data centres, not consumer networks, so absolute values are
lower than an end user would see — the comparison between providers is the meaningful
part. Provider coverage changes over time as APIs appear and shut down.

## Citation

Archived, citable version with a DOI: <https://doi.org/10.5281/zenodo.21954788>

```bibtex
@dataset{llmlatency_tracker,
  title  = {LLM Latency Tracker: measured latency and uptime for AI inference APIs},
  author = {llmlatency.dev},
  year   = {2026},
  doi    = {10.5281/zenodo.21954788},
  url    = {https://llmlatency.dev}
}
```

## Links

- Live site and methodology: <https://llmlatency.dev>
- Machine-readable API: <https://llmlatency.dev/api/rankings.json>
- Daily snapshots in git: <https://github.com/mazamaka/llm-latency-tracker>
- Python client: <https://pypi.org/project/llmlatency/>
- Citable archive (DOI): <https://doi.org/10.5281/zenodo.21954788>

Licence: **CC-BY-4.0**. Snapshot generated 2026-08-18.