{
 "schema_version": 1,
 "generated": "2026-10-31",
 "id": "ggml-org-whisper-cpp--shrink-whisper-models-with-quantization",
 "repo": "ggml-org/whisper.cpp",
 "repo_url": "https://github.com/ggml-org/whisper.cpp",
 "repo_slug": "ggml-org-whisper-cpp",
 "title": "Run bigger Whisper models on small hardware with quantization",
 "page_title": "How to run bigger Whisper models on small hardware with quantization with Whisper CPP",
 "summary": "Quantize a ggml Whisper model to Q5_0 so it uses less memory and disk with the same commands.",
 "who": "Someone transcribing on a Raspberry Pi, an old laptop or a small server where the full model barely fits.",
 "problem": "The more accurate Whisper models need gigabytes of memory, which rules them out on modest machines.",
 "outcome": "A quantized model file that whisper-cli loads like any other, using less memory and disk space.",
 "steps": [
  "Build Whisper CPP with `cmake -B build` and `cmake --build build -j --config Release`",
  "Download the model you want to shrink, for example with `sh ./models/download-ggml-model.sh base.en`",
  "Quantize it: `./build/bin/quantize models/ggml-base.en.bin models/ggml-base.en-q5_0.bin q5_0`",
  "Run the quantized model: `./build/bin/whisper-cli -m models/ggml-base.en-q5_0.bin ./samples/gb0.wav`",
  "Compare speed and accuracy against the original on a few of your own files before switching"
 ],
 "agent_prompt": "Using ggml-org/whisper.cpp, quantize the <model> ggml model to q5_0 with the quantize tool, then transcribe <test files> with both the original and the quantized model. Report memory use, run time and any differences in the transcripts.",
 "agents": [
  "claude-code",
  "codex",
  "cursor"
 ],
 "difficulty": "Intermediate",
 "time": "30 minutes",
 "basis": "readme",
 "caveat": "Quantization trades a little accuracy for size, so check transcripts on your own audio before relying on it.",
 "category": "Content",
 "tags": [
  "Content"
 ],
 "lang": "c++",
 "requirements": [
  "A C/C++ toolchain and CMake to build from source",
  "ffmpeg to convert audio to 16-bit WAV, since whisper-cli reads 16-bit WAV files",
  "Disk and RAM for the model you pick: about 142 MiB and 388 MB for base, up to 2.9 GiB and 3.9 GB for large",
  "Optional: Xcode command line tools and Python 3.11 for Core ML on Apple Silicon"
 ],
 "risk": "none",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [],
 "best": false,
 "score": 0.9,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/ggml-org-whisper-cpp/shrink-whisper-models-with-quantization/",
 "md": "https://dedupedai.com/use-cases/ggml-org-whisper-cpp/shrink-whisper-models-with-quantization/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/ggml-org-whisper-cpp--shrink-whisper-models-with-quantization.json",
 "api_version": "v1"
}