AI tool comparison
ClawBench vs Perplexity
Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.
Research
ClawBench
153 real-world browser tasks, live websites — best AI agent scores only 33%
75%
Panel ship
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Community
Free
Entry
ClawBench is a browser agent evaluation framework built around 153 real-world tasks running on 144 live production websites — not simulated environments or curated sandboxes. Tasks span e-commerce, travel booking, SaaS dashboards, government portals, and developer tools. A built-in request interceptor blocks genuinely irreversible actions (payments, form submissions that send data) so evaluations can run safely on real sites. The benchmark records five layers of data per run: session replays, screenshots at each decision point, raw HTTP traffic, agent reasoning traces, and browser action sequences. This makes failure analysis tractable — you can see exactly which DOM element the agent misidentified, not just a final score. The dataset is open and the evaluation harness is reproducible. The headline finding is sobering: Claude Sonnet 4.6, the best performer, completes only 33.3% of tasks. GLM-5 is second at 24.2%. No model exceeds 50% on any individual task category. The implication is stark — current browser agents are far from autonomous on the open web, and the gap between benchmark performance and production performance is still enormous.
Search & Research
Perplexity
AI research platform with cited answers, deep research, and shareable pages
100%
Panel ship
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Community
Free
Entry
Perplexity evolved from search-with-citations into a full research platform. Deep Research runs multi-step investigations that take 2–5 minutes and produce comprehensive reports with sources — replacing hours of manual research. Perplexity Pages creates shareable, structured research documents anyone can read. Pro Search includes access to Claude, GPT-4o, and Sonar models for different task types. Shopping mode surfaces product comparisons with price tracking. The answer engine that replaced Google Search for research-heavy workflows.
Reviewer scorecard
“The five-layer recording (replays, HTTP traffic, reasoning traces) is the right approach for actual debugging — finally a benchmark where failure analysis is tractable. The 33% score also sets honest expectations for teams planning to ship production browser agents right now.”
“Deep Research is legitimately impressive for technical evaluation — comparing libraries, auditing security postures, understanding architecture decisions. What used to take 2 hours of reading docs and Stack Overflow now takes 5 minutes and comes with citations I can verify.”
“Live website testing is a double-edged sword: sites change their DOM, anti-bot measures evolve, and a task that passes today may fail next week with no code change. Benchmark drift on live websites could make ClawBench scores meaningless over 6-month periods without constant maintenance.”
“Citations remain the core differentiator vs ChatGPT. Every claim is sourced and you can click through. Hallucination risk drops dramatically when the model knows it has to cite. Deep Research is good but sometimes slow — it works best when you have a few minutes, not seconds.”
“33% on live websites is actually more impressive than it sounds given the adversarial diversity of the real web. The trajectory from 5% in 2024 to 33% in 2026 means we're likely crossing 60% in 18 months — at which point browser agents start displacing RPA software at scale.”
“Perplexity Pages is the underrated bet — turning AI research into shareable documents is how knowledge workers will collaborate in the future. The roadmap (Deep Research, Pages, shopping, Pro with multiple models) is building the AI-native knowledge platform, not just a better search engine.”
“As someone who uses browser agents for research and competitor monitoring, the failure mode analysis is exactly what I need. Knowing which website categories agents handle well (dev tools) vs. poorly (government portals) helps me route tasks appropriately right now.”
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