llm-speed
LLM speed benchmarks: measured tok/s with source runs
The benchmark suite for local + hosted LLM inference.
Run it. See your tok/s. Compare your rig.
$ pipx install llm-speed && llm-speed benchUses your installed models and backends. Open source. First benchmark? Follow the setup steps.
See a signed 467 tok/s runLLM speed test FAQ
Where can I find community-submitted LLM speed benchmarks?
llm-speed.com is a community LLM speed benchmark: the open dataset holds 522 measured results from 277 public runs across 71 models and 28 hardware configurations, each linked to its signed source run.
How do I run an LLM speed test on my own machine?
Install the open-source CLI and run the suite: pipx install llm-speed && llm-speed bench. It measures decode tok/s, prefill and time to first token on fixed workloads and adds your signed run to the leaderboard.
Choose a model. Understand the wait.
Start with measured configurations, exact downloads, or a check of your current setup.
Qwen3.8 vs Gemma 4 on RTX 5090Six source runs: speed, first-token wait, memory and exact files. Compare the tested configurations.Why is my local LLM slow?Check GPU offload, model loading, context and caching before spending on more hardware.Which model should I download for my Mac?Qwen3.8 and GLM-5.3 MLX files with download sizes, runtime requirements and memory limitations.
Latest LLM benchmarks
20 runs · suite-v1- RTX 5090 (32GB) + AMD EPYC 7543 32-Core Processor (120c) + 945GB
- RTX 5090 (32GB) + AMD EPYC 7543 32-Core Processor (120c) + 945GB
- RTX 5090 (32GB) + AMD EPYC 7543 32-Core Processor (120c) + 945GB
- RTX 5090 (32GB) + AMD EPYC 7543 32-Core Processor (120c) + 945GB
- RTX 5090 (32GB) + AMD EPYC 7543 32-Core Processor (120c) + 945GB
- 2x RTX 3090 (24GB) + AMD EPYC 7H12 64-Core Processor (128c) + 1008GB
- RTX 3090 (24GB) + AMD EPYC 7282 16-Core Processor (16c) + 126GB
- RTX 3090 (24GB) + AMD EPYC 7282 16-Core Processor (16c) + 126GB
- RTX 3090 (24GB) + AMD EPYC 7282 16-Core Processor (16c) + 126GB
- RTX 3090 (24GB) + AMD EPYC 7282 16-Core Processor (16c) + 126GB
- RTX 3090 (24GB) + AMD EPYC 7282 16-Core Processor (16c) + 126GB
- A40 (45GB) + Intel(R) Xeon(R) Gold 6342 CPU @ 2.80GHz (48c) + 504GB
- RTX 4090 (24GB) + AMD EPYC 75F3 32-Core Processor (64c) + 504GB
- RTX 4090 (24GB) + AMD EPYC 7642 48-Core Processor (48c) + 252GB
- RTX 4090 (24GB) + AMD EPYC 7642 48-Core Processor (48c) + 252GB
- RTX 3090 (24GB) + AMD Ryzen Threadripper PRO 5975WX 32-Cores (32c) + 504GB
- RTX 3090 (24GB) + AMD Ryzen Threadripper PRO 5975WX 32-Cores (32c) + 504GB
- 3x A100 (80GB) + AMD EPYC 7742 64-Core Processor (128c) + 1008GB
- RTX A4000 (16GB) + AMD EPYC 7402P 24-Core Processor (24c) + 126GB
- RTX 5090 (32GB) + AMD EPYC 9534 64-Core Processor (128c) + 756GB
Explore local-LLM speed
Will it run — and how fast?Check any model + quant against your GPU or Mac, with the real measured tok/s.Buying guidesBest GPU, Mac, or rig for local LLMs — ranked on signed runs with linked source data.Head-to-headRTX 5090 vs 4090, Apple vs NVIDIA, model vs model — decode tok/s side by side.Speed cheatsheetDecode tok/s for every model × hardware cell we have data for.Community reports vs signed2,176 tok/s claims from r/LocalLLaMA & HN, next to our measured numbers.FAQHow fast is usable? Does quantization cost speed? Why is long context slow?BlogLong-form on local-LLM speed, grounded in signed benchmark runs.