Datasets:

llmspeed
/

llm-speed-benchmarks

license: cc-by-4.0
language:
  - en
pretty_name: llm-speed inference-speed benchmarks
tags:
  - llm
  - inference
  - benchmark
  - gpu
  - apple-silicon
  - tokens-per-second
size_categories:
  - n<1K
configs:
  - config_name: default
    data_files:
      - split: runs
        path: runs.csv

llm-speed: signed LLM inference-speed benchmarks

Crowdsourced, cryptographically signed measurements of how fast large language models actually run: decode tokens per second, time to first token, and latency, across consumer GPUs, Apple Silicon, and hosted APIs, under one reproducible workload suite (suite-v1).

Live data and bulk downloads: https://llm-speed.com/data
Per-run permalink: https://llm-speed.com/r/<id>
Methodology: https://llm-speed.com/methodology
DOI: https://doi.org/10.5281/zenodo.21254813 (Zenodo archive; resolves to the latest version)
License: CC BY 4.0. Reuse freely, including commercially, with attribution and a link back.

What is in it

Each row is the headline result of one signed benchmark run.

column	meaning
`id`	the run id
`permalink`	citable page for the run on llm-speed.com
`suite_version`	workload suite version (currently suite-v1)
`top_model_name`	model that was measured
`top_backend`	ollama, llama.cpp, mlx, vllm, exllamav2, and so on
`top_workload`	which workload produced the headline number
`accelerator_summary`	the GPU or Apple Silicon plus host
`top_decode_tps`	headline decode tokens per second
`received_at`	when the run was submitted

Full per-workload detail (prefill tok/s, TTFT, quantization, percentiles) for any run is at https://llm-speed.com/r/<id> and via the live API at https://api.llm-speed.com/v1/results/<id>. Files: runs.csv, runs.jsonl, runs.json, plus meta.json (counts and generation timestamp).

How it is measured

Every run is produced by the open-source llm-speed CLI under the suite-v1 workload set, fingerprinted to real hardware, and cryptographically signed on upload (EdDSA/JWS) so a number cannot be edited after the fact. The values are measured, not modeled. If two rows disagree for the same model and hardware, both are real submissions from different setups; open each permalink to see the raw workload detail.

Citation

llm-speed. The llm-speed dataset: signed LLM inference-speed benchmarks.
Zenodo (2026). https://doi.org/10.5281/zenodo.21254813. CC BY 4.0.