Model Download Time Calculator
How long a checkpoint takes to pull at your bandwidth — with the real-world Hub throttle and resume math.
ISPs sell megaBITS, files come in gigaBYTES — divide by 8 before anything else. Use hf_transfer (Rust multi-stream) or aria2c to push efficiency toward 90% on fast lines; single-stream Python often caps near 40 MB/s.
Formula
About Model Download Time Calculator
The night before the demo, the question is always the same: can I still download the 70B in time? This calculator does the honest math — your advertised megabits divided by eight, times a realistic efficiency factor for CDN throttling and disk writes — and answers in minutes or hours. The defaults price Llama-3-8B FP16 on a 300 Mbps line (about ten minutes done right). The note's tooling advice matters more than the formula: a single-stream Python download can be 3× slower than hf_transfer on the same connection.
How to use Model Download Time Calculator
- 1Enter your values into Model Download Time Calculator — sensible, domain-typical defaults are pre-filled so you see a real result immediately.
- 2The result recomputes live using the formula shown on the page; there is no button to press.
- 3Adjust any input to compare scenarios, then read the worked example to see the substituted numbers.
Why use Model Download Time Calculator?
- ✓Computes Model Download Time instantly in your browser — no sign-up, no upload, no server round-trip.
- ✓100% free and unlimited, with the exact formula shown: time = size ÷ (Mbps ÷ 8 × efficiency) — note the bits-vs-bytes factor of 8 that wrecks every first estimate.
- ✓Runs entirely client-side, so every value you enter stays private on your device.
- ✓Live recompute as you type, with a worked example and authoritative references for trust.
Frequently asked questions
Why is my download so much slower than my internet plan?+
Three stacked taxes: bits→bytes (÷8), single-TCP-stream throughput limits to a distant CDN (often 30–50 MB/s regardless of your line), and disk write contention. Multi-stream downloaders (hf_transfer, aria2c -x16) reclaim most of it.
Which model files do I actually need?+
For inference, just the safetensors shards plus config/tokenizer — skip .bin duplicates, optimizer states (*.pt training checkpoints can DOUBLE the bytes) and unused precision variants. huggingface-cli download with allow_patterns saves real hours.
Can I resume a broken 40 GB download?+
Yes — the Hub serves ranged requests and huggingface_hub caches per-shard with resume; aria2c and wget -c likewise. The worst case is a single huge GGUF where a corrupt tail forces a re-pull — prefer sharded repos on flaky connections.
Is it faster to download quantized?+
Almost always: a Q4_K_M is ~30% the FP16 bytes — a 70B drops from 141 GB to ~40 GB, hours saved. If you intend to quantize locally anyway, downloading the pre-quantized artifact wins unless you specifically need to run your own calibration.
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