{
 "schema_version": 1,
 "generated": "2026-10-26",
 "id": "nicorobinreal-llmspeed--submit-a-real-benchmark-result",
 "repo": "nicorobinreal/llmspeed",
 "repo_url": "https://github.com/nicorobinreal/llmspeed",
 "repo_slug": "nicorobinreal-llmspeed",
 "title": "Submit a real llama-bench result as a pull request",
 "page_title": "How to submit a real llama-bench result as a pull request with Llmspeed",
 "summary": "Run llama-bench on your machine and add a verified row to the benchmark CSV.",
 "who": "A local LLM user with a GPU or Mac who wants to improve the accuracy of Llmspeed estimates for hardware others also own.",
 "problem": "Estimates for some hardware and models are modeled rather than measured, so real measurements are the most valuable contribution.",
 "outcome": "A pull request that appends your measured row to the benchmark file, with the full llama-bench output attached.",
 "steps": [
  "Run `llama-bench -m your-model.gguf -p 512 -n 128` on your machine.",
  "Fill one row with hardware, model, quant, backend, engine_version, gen_tps, prefill_tps, prompt_tokens, source_url and notes.",
  "Append the row to benchmarks/submissions.csv in a fork of the repo.",
  "Open a pull request and paste the full llama-bench output into the PR description.",
  "Link a post, issue or gist with the full output in the source_url column."
 ],
 "agent_prompt": "In the llmspeed repo (github.com/nicorobinreal/llmspeed), run `llama-bench -m <model.gguf> -p 512 -n 128` and append one row to benchmarks/submissions.csv. Expected output: a pull request with one new CSV row and the full llama-bench output in the description. Verify that gen_tps matches the tg128 result and prefill_tps matches the pp512 result.",
 "agents": [
  "any"
 ],
 "difficulty": "Advanced",
 "time": "1 hour",
 "basis": "readme",
 "caveat": "The README asks for the full llama-bench output in the PR description, so a row without it may not be accepted.",
 "category": "Money",
 "tags": [
  "Money"
 ],
 "lang": "typescript",
 "requirements": [
  "A web browser to use llmspeed.dev",
  "For contributing a benchmark: a machine with llama.cpp and a .gguf model file",
  "For local development: npm"
 ],
 "risk": "none",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [],
 "best": false,
 "score": 0.8,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/nicorobinreal-llmspeed/submit-a-real-benchmark-result/",
 "md": "https://dedupedai.com/use-cases/nicorobinreal-llmspeed/submit-a-real-benchmark-result/index.md",
 "disclaimer": "Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked \"Seen in the wild\", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email hello@dedupedai.com and we will look at it promptly.",
 "api": "https://dedupedai.com/api/v1/usecases/nicorobinreal-llmspeed--submit-a-real-benchmark-result.json",
 "api_version": "v1"
}