The pitch is simple and the execution matches it: llmspeed is a lookup table that pairs hardware with models and shows you the inference speed you'd actually get. No synthetic benchmarks divorced from reality, no YouTuber telling you a card is 'blazing fast' — just tokens-per-second estimates you can read before you buy. The tool covers roughly 30 hardware configurations — from a lowly MacBook M2 Pro 16GB up through an H200 141GB cloud instance — crossed against roughly 15 models ranging from Llama 3.1 8B to DeepSeek V4 Flash. Measured numbers come from community benchmarks (r/LocalLLaMA, localscore.ai); the rest are projected from specs or interpolated from similar setups. The site is open source on GitHub. What makes this useful rather than just nice is the 'feel' framing. Tokens per second is an abstract number until you've sat in front of a model that streams at 8 tok/s versus one that streams at 45 tok/s. The former feels like talking to someone on a bad phone line; the latter feels like a fast typist. llmspeed bridges that gap by letting you browse configurations side-by-side before committing money. The hardware list reads like a census of the current local-inference landscape: NVIDIA's full RTX 30/40/50 stack, AMD's RX 7900 and new 9070 XT, Apple Silicon from M2 Pro through M5 Ultra, Intel Arc Pro, AMD's Strix Halo APU, and even a CPU-only Ryzen 9 baseline. The model list skews toward the latest open-weight releases — Qwen 3.x, Gemma 4, DeepSeek R1 and V4, Ornith 1.5, GPT-OSS — which is where the local community's attention actually sits right now. The obvious limitation is data provenance. 'Measured numbers come from community benchmarks; others are derived from similar setups or projected from specs' is an honest disclaimer, but it means some cells in the matrix are educated guesses, not measurements. The site doesn't yet distinguish measured from projected entries visually, which is the single biggest improvement it could make. As a community tool, llmspeed occupies the same niche as UserBenchmark once did for gaming GPUs — a quick-and-dirty comparison layer that saves you from reading fifteen forum threads. The difference is that the local LLM space moves faster and the variables are weirder (VRAM matters more than raw FLOPS, quantization format changes everything, prompt length shifts the curve). A static lookup table will need aggressive updating to stay useful. Still, for what it is — a free, open-source, browsable matrix that answers 'will Qwen 3 30B run acceptably on my 4070 Ti Super?' — it fills a gap that no official benchmark suite or hardware vendor currently fills. The value is in the curation, not the technology.
