--- license: cc-by-4.0 pretty_name: "localLLMrig open data: local LLM memory needs, hardware and EU GPU prices" language: [en] tags: [local-llm, vram, gpu, llama.cpp, quantization, hardware, benchmark, prices] size_categories: [1K **Estimates are not measurements.** Every memory figure and every `est_decode_tok_s` value comes from a published formula (see [METHOD.md](METHOD.md)). The only measured speeds are the showdown CPU numbers (one run, CPU-only cloud VM, not representative of GPU speed) and the third-party community rows, which are labelled with their source. ## Files | File | Rows | What it is | |---|---|---| | `data/models.csv` | 12 | Model architecture (layers, KV heads, head dim, max context) and estimated memory need at 8,192 tokens for Q4_K_M, Q5, Q8 and FP16. | | `data/hardware.csv` | 29 | GPUs, PC builds, Macs and laptops: memory, bandwidth (with source where stated), price in EUR incl. VAT with label, date and source URL. USD is an FX estimate. | | `data/gpu-price-per-gb-vram.csv` | 7 | Single cards ranked by EUR per GB of VRAM. Used medians and new in-stock lows are labelled; do not compare them as if they were the same thing. | | `data/fit-estimates.csv` | 1,392 | Every model × hardware × quant: estimated need, assumed usable memory, fit (`full`, `offload`, `no`, `unscored`) and estimated decode tok/s. | | `data/community-measurements.csv` | 3 | Third-party measurements quoted on the site, with source and caveats. Not localLLMrig measurements. | | `data/showdown/` | 6 models × 10 prompts | Free LLM Showdown (17 Oct 2026): prompts, full unedited outputs, hand checks on 4 objective prompts, CPU speeds, GGUF files with sha256. | | `data/localllmrig-data.json` | — | Everything above in one JSON file, plus the formula constants. | | `snapshot/` | — | Raw inputs: `/api/models` and `/api/hardware` as fetched on 2026-10-17, and the showdown JSON. | | `scripts/build.py` | — | Rebuilds `data/` from `snapshot/` (or `--fetch` from the live API). Python 3 standard library only. | | `scripts/validate.py` | — | Cross-checks the fit/speed matrix against the live `/api/recommend` endpoint. | ## Quick start ```bash python3 scripts/build.py # rebuild from the snapshot python3 scripts/build.py --fetch # refresh from https://localllmrig.com/api/* python3 scripts/validate.py # compare with the live recommender ``` ```python import pandas as pd fit = pd.read_csv("data/fit-estimates.csv") fit.query("model_id == 'qwen2.5-32b' and quant == 'Q4' and fit == 'full'") ``` ## Snapshot - Prices: as of 14–17 Oct 2026 (per row `price_as_of`). Prices move; check the source URL before buying anything. - Formula version: localLLMrig `lib/formula.ts`, priceAsOf 2026-10-14. - Showdown run: 17 Oct 2026, llama.cpp b11707, Q4_K_M GGUFs, temperature 0. ## Cite Archived on Zenodo: version DOI [10.5281/zenodo.23535233](https://doi.org/10.5281/zenodo.23535233) (snapshot 2026-10-21); concept DOI [10.5281/zenodo.23535232](https://doi.org/10.5281/zenodo.23535232) (always resolves to the latest version). ``` localLLMrig (2026). localLLMrig open data: local LLM memory, hardware and EU GPU prices (snapshot 2026-10-17). https://localllmrig.com. CC BY 4.0. https://doi.org/10.5281/zenodo.23535232 ``` See also [CITATION.cff](CITATION.cff). ## Licensing notes - The compilation, formula outputs and documentation are CC BY 4.0. - Showdown answers are outputs of third-party models. Each model's own license applies to use of that model (see `license` and `license_url` in `data/showdown/speeds-2026-10-17.csv`). Llama 3.2 is licensed under the Llama 3.2 Community License, Copyright © Meta Platforms, Inc. All Rights Reserved. Gemma is provided under the Gemma Terms of Use (ai.google.dev/gemma/terms). - Prices are facts recorded from the named public sources, with links. Spec figures link to vendor pages where available. ## Corrections Open an issue with the row, what is wrong, and a source link. Corrections are applied to the site and the next snapshot.