GGUF Metadata Reader (Browser)

A single-file, static web app to read GGUF model metadata directly in the browser and estimate memory usage (RAM/VRAM) for a chosen context window and KV cache quantization.

• Works with remote URLs that support HTTP Range requests (e.g., many Hugging Face files)
• Works with local .gguf files (drag-and-drop via file picker)
• Detects sharded models (e.g., -00001-of-00013) and sums total size
• No server required; everything runs client-side

Quick Start

Option A: Open the file directly

1. Open index.html in a modern browser (Chrome, Edge, Safari).
2. Paste a GGUF URL or choose a local .gguf file and click the corresponding button.

Option B: Serve locally (helps with some CORS setups)

cd path/to/model-memory-calculator
python -m http.server 8000
# Then open http://localhost:8000 in your browser

Usage

• GGUF URL: Paste a direct link to a .gguf (e.g., a Hugging Face “resolve/main” URL). Many hosts allow partial download via HTTP Range.
• Or choose a local GGUF file: Uses the browser’s File API; no upload leaves your machine.
• Context size (tokens): Select the desired context window (e.g., 4K, 16K, 128K).
• KV cache quantization: Choose how keys/values are stored in memory. Options show approximate bytes per value.
• Verbose: Prints debug logs of what’s read and how size is determined.

Click “Read URL” or “Read File”. If successful, you’ll see:

• Extracted params: attention_heads, kv_heads, hidden_layers, hidden_size, split_count (if present)
• Memory estimate: model size + KV cache size at your chosen context/quantization

How It Works

• GGUF parsing: Reads just enough of the GGUF header to extract:
  • .attention.head_count
  • .attention.head_count_kv
  • .block_count
  • .embedding_length
  • split.count (if present)
• Remote file size:
  • Tries HEAD to get Content-Length.
  • Falls back to a Range: bytes=0-0 request and reads Content-Range.
• Sharded models:
  • Detects -00001-of-000NN style patterns in URLs or uses split.count metadata.
  • Sums sizes across parts (remote) or estimates total from a single shard (local) when possible.
• KV cache estimate:
  • Uses a simplified formula: bytes_per_value × hidden_size × hidden_layers × context_tokens.
  • Shows total as: Model + KV (MB/GB). Actual usage can vary by backend/implementation.

Notes & Limitations

• GGUF versions: Supports GGUF v1–v3 headers for the fields listed above.
• CORS & Range: Remote hosts must allow cross-origin requests and HTTP Range. If not, size detection may fail; download the file and use the local option instead.
• Range ignored: Some servers respond 200 without honoring Range. The app avoids downloading the full body for size only; estimates can fail in this case.
• Sanity limits: Very long strings/arrays in metadata are bounded to avoid huge reads.
• Estimates only: KV cache math is intentionally simplified. Different runtimes store KV differently (e.g., layout, precision, per-head factors).

Troubleshooting

• “Failed to read params.”
  • The file may not be GGUF or uses unsupported/unexpected metadata. Try another file or update the URL.
• “Could not determine file size or compute usage (CORS/Range?).”
  • The remote host may block CORS or not report size via HEAD/Range. Try serving the page locally, a different host, or the local file picker.
• Split detection issues
  • Ensure URLs use a stable pattern (e.g., -00001-of-000xx) or that split.count is present in metadata.

Privacy

• The local file option never uploads your file; parsing happens entirely in your browser.
• For remote URLs, the app performs small range requests to read the header and determine file size. It aborts early once required metadata is read.

Development

• No build step required. The app is a single page:
  • index.html — All logic and UI
• Open in a browser or serve with any static server.

License

This project is licensed under the terms in LICENSE.