Post · Benchmarks & research
Jev on the WebMCP benchmark
Jev picks the tool, a fast LLM fills the arguments: 49 of 49 tasks solved.
Open x.com ↗We just ran Jev on our WebMCP benchmark.
The result: basically broke the benchmark.
Jev + Mercury 2.5 (a fast, low-cost LLM) using WebMCP solved 100% of the tasks at roughly 112× lower model cost than GPT-6 Astra using computer use with code execution. Compared to Astra using
How builders describe it
The WebMCP benchmark author reports that Jev paired with the small Mercury 2.5 model solved 100% of tasks at roughly 112x lower model cost than GPT-6 Astra with computer use.
The decision Jev makes
Benchmark questions with known answers, to check accuracy and confidence.
Where it fits
Head-to-head tests, calibration studies and independent research into how well Jev decides, how fast, and at what cost. All 682 benchmarks & research projects →
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