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Replaces the previous benchmarks/README.md, which claimed specific numbers (94.2% accuracy, 0.8ms extraction, 97% Cloudflare bypass, etc.) with no reproducing code committed to the repo. The `webclaw-bench` crate and `benchmarks/fixtures`, `benchmarks/ground-truth` directories it referenced never existed. This is what #18 was calling out. New benchmarks/ is fully reproducible. Every number ships with the script that produced it. `./benchmarks/run.sh` regenerates everything. Results (18 sites, 90 hand-curated facts, median of 3 runs, webclaw 0.3.18, cl100k_base tokenizer): tool reduction_mean fidelity latency_mean webclaw 92.5% 76/90 (84.4%) 0.41s firecrawl 92.4% 70/90 (77.8%) 0.99s trafilatura 97.8% 45/90 (50.0%) 0.21s webclaw matches or beats both competitors on fidelity on all 18 sites while running 2.4x faster than Firecrawl's hosted API. Includes: - README.md — headline table + per-site breakdown - methodology.md — tokenizer, fact selection, run rationale - sites.txt — 18 canonical URLs - facts.json — 90 curated facts (PRs welcome to add sites) - scripts/bench.py — the runner - results/2026-04-17.json — today's raw data, median of 3 runs - run.sh — one-command reproduction Closes #18 Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
94 lines
4.1 KiB
Markdown
94 lines
4.1 KiB
Markdown
# Benchmarks
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Reproducible benchmarks comparing `webclaw` against open-source and commercial
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web extraction tools. Every number here ships with the script that produced it.
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Run `./run.sh` to regenerate.
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## Headline
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**webclaw preserves more page content than any other tool tested, at 2.4× the
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speed of the closest competitor.**
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Across 18 production sites (SPAs, documentation, long-form articles, news,
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enterprise marketing), measured over 3 runs per site with OpenAI's
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`cl100k_base` tokenizer. Last run: 2026-04-17, webclaw v0.3.18.
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| Tool | Fidelity (facts preserved) | Token reduction vs raw HTML | Mean latency |
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|---|---:|---:|---:|
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| **webclaw `--format llm`** | **76 / 90 (84.4 %)** | 92.5 % | **0.41 s** |
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| Firecrawl API (v2, hosted) | 70 / 90 (77.8 %) | 92.4 % | 0.99 s |
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| Trafilatura 2.0 | 45 / 90 (50.0 %) | 97.8 % (by dropping content) | 0.21 s |
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**webclaw matches or beats both competitors on fidelity on all 18 sites.**
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## Why webclaw wins
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- **Speed.** 2.4× faster than Firecrawl's hosted API. Firecrawl defaults to
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browser rendering for everything; webclaw's in-process TLS-fingerprinted
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fetch plus deterministic extractor reaches comparable-or-better content
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without that overhead.
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- **Fidelity.** Trafilatura's higher token reduction comes from dropping
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content. On the 18 sites tested it missed 45 of 90 key facts — entire
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customer-story sections, release dates, product names. webclaw keeps them.
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- **Deterministic.** Same URL → same output. No LLM post-processing, no
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paraphrasing, no hallucination risk.
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## Per-site results
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Numbers are median of 3 runs. `raw` = raw fetched HTML token count.
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`facts` = hand-curated visible facts preserved out of 5 per site.
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| Site | raw HTML | webclaw | Firecrawl | Trafilatura | wc facts | fc facts | tr facts |
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|---|---:|---:|---:|---:|:---:|:---:|:---:|
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| openai.com | 170 K | 1,238 | 3,139 | 0 | **3/5** | 2/5 | 0/5 |
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| vercel.com | 380 K | 1,076 | 4,029 | 585 | **3/5** | 3/5 | 3/5 |
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| anthropic.com | 103 K | 672 | 560 | 96 | **5/5** | 5/5 | 4/5 |
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| notion.com | 109 K | 13,416 | 5,261 | 91 | **5/5** | 5/5 | 2/5 |
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| stripe.com | 243 K | 81,974 | 8,922 | 2,418 | **5/5** | 5/5 | 0/5 |
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| tavily.com | 30 K | 1,361 | 1,969 | 182 | **5/5** | 4/5 | 3/5 |
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| shopify.com | 184 K | 1,939 | 5,384 | 595 | **3/5** | 3/5 | 3/5 |
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| docs.python.org | 5 K | 689 | 1,623 | 347 | **4/5** | 4/5 | 4/5 |
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| react.dev | 107 K | 3,332 | 4,959 | 763 | **5/5** | 5/5 | 3/5 |
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| tailwindcss.com/docs/installation | 113 K | 779 | 813 | 430 | **4/5** | 4/5 | 2/5 |
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| nextjs.org/docs | 228 K | 968 | 885 | 631 | **4/5** | 4/5 | 4/5 |
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| github.com | 234 K | 1,438 | 3,058 | 486 | **5/5** | 4/5 | 3/5 |
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| en.wikipedia.org/wiki/Rust | 189 K | 47,823 | 59,326 | 37,427 | **5/5** | 5/5 | 5/5 |
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| simonwillison.net/…/latent-reasoning | 3 K | 724 | 525 | 0 | **4/5** | 2/5 | 0/5 |
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| paulgraham.com/essays.html | 2 K | 169 | 295 | 0 | **2/5** | 1/5 | 0/5 |
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| techcrunch.com | 143 K | 7,265 | 11,408 | 397 | **5/5** | 5/5 | 5/5 |
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| databricks.com | 274 K | 2,001 | 5,471 | 311 | **4/5** | 4/5 | 4/5 |
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| hashicorp.com | 109 K | 1,501 | 4,289 | 0 | **5/5** | 5/5 | 0/5 |
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## Reproducing this benchmark
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```bash
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cd benchmarks/
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./run.sh
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```
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Requirements:
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- Python 3.9+
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- `pip install tiktoken trafilatura firecrawl-py`
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- `webclaw` release binary at `../target/release/webclaw` (or set `$WEBCLAW`)
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- Firecrawl API key (free tier: 500 credits/month, enough for many runs) —
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export as `FIRECRAWL_API_KEY`. If omitted, the benchmark runs with webclaw
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and Trafilatura only.
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One run of the full suite burns ~60 Firecrawl credits (18 sites × 3 runs,
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plus Firecrawl's scrape costs 1 credit each).
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## Methodology
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See [methodology.md](methodology.md) for:
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- Tokenizer rationale (`cl100k_base` → covers GPT-4 / GPT-3.5 /
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`text-embedding-3-*`)
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- Fact selection procedure and how to propose additions
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- Why median of 3 runs (CDN / cache / network noise)
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- Raw data schema (`results/*.json`)
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- Notes on site churn (news aggregators, release pages)
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## Raw data
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Per-run results are committed as JSON at `results/YYYY-MM-DD.json` so the
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history of measurements is auditable. Diff two runs to see regressions or
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improvements across webclaw versions.
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