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Launch teardown: llmspeed

Unsolicited sample, not an endorsement. Ship Plainly made this as a portfolio example from public information only. The maker hasn't seen, asked for, or approved it, and isn't affiliated with us. Facts are from the sources below as read Oct 17, 2026 (~11:30 AM CDT).

Sources (public)

What the public pages say: You pick hardware and a model, and it "simulates tokens/sec and time-to-first-token from verified benchmarks for GPUs, Macs, and more." Measured numbers come from community benchmarks (r/LocalLLaMA, localscore.ai and more). Others are "derived from similar setups or projected from specs." It's open source.

What the HN thread asked for (paraphrased): whether the numbers match real use (one commenter reported their M2 Ultra running faster than the listed M3 Ultra estimate), harness/library versions per benchmark, multi-GPU and hybrid setups, PCIe generation, prefill speed for agentic coding, and older cards like the RX580. The maker replied, asked for model/quant details, and shipped new benchmarks during the thread.


1. Teardown: what's working, what we'd change

Working:

What we'd change:

  1. Lead with trust, because accuracy is the #1 objection. The site already separates "measured" from "derived/projected", but that note lives in small print. Put a measured-vs-projected badge on every result and link each measured number to its source.
  2. Name the buyer moment. "Before you buy" is right. Make it concrete: "Thinking about a 5090, a Mac Studio, or a used 3090? Feel each one first."
  3. Prefill is the next headline. Agentic-coding users said time-to-first-token on long prompts matters more than output speed. If it's on the roadmap, say so.
  4. The crawlable page text is one sentence. The page is a JS app, so search engines and AI answer engines see little. Add a short static "How the numbers work" section and an FAQ.

7. Hero rewrite

Full sample kit (Product Hunt set, X thread, Show HN notes): read it here.


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