Show HN: Llmspeed – feel how fast a local LLM runs before you buy the hardware
Points and comments are a snapshot, not live.
Llmspeed lets you estimate local LLM speed for specific hardware and models before purchasing.
The tool lets users pick hardware (e.g., RTX 4090, Mac Studio M5 Ultra) and a model (e.g., Llama 3.1 8B, Qwen 3.5 9B) to see estimated tokens per second and time to first token. Numbers come from community benchmarks (r/LocalLLaMA, localscore.ai) or are projected from specs for a short prompt on a single device. The site lists dozens of hardware configs and models, with a race feature to compare configurations.
Estimates are for a single device only; multi-GPU setups are not yet supported. The project is open source on GitHub.
What commenters are saying
Commenters praised the concept but raised accuracy concerns. One user reported their M2 Ultra 128GB runs almost twice as fast as the site's M3 Ultra 512GB estimate. Another noted the site omits older GPUs like the RX 580, which can run Qwen 9B models at usable speeds (20 t/s). Several users wanted multi-GPU support, PCIe gen selection, and Nvlink options. A key point: prefill speed for agentic coding matters more than output token speed. One commenter runs a 35B MoE model at 16-19 t/s on a GTX 1070 Max-Q, challenging the site's assumptions about hardware limits.