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Benchmark profile

Multi-Environment Web Challenge (MEWC)

A benchmark that evaluates AI agents on multi-environment web challenges, testing navigation and task completion across diverse live web environments.

Data verified

Benchmark score on MEWC — July 23, 2026

BenchLM mirrors the published score view for MEWC. MiniMax M2.5 leads the public snapshot at 74.4%. BenchLM does not use these results to rank models overall.

1 modelAgenticCurrentDisplay onlyUpdated July 23, 2026

Benchmark score table (1 model)

Score
1
MiniMax M2.5MiniMax · Closed
74.4%

About MEWC

Year

2026

Tasks

Web-agent tasks

Format

Browser task completion

Difficulty

Open-web agent workflows

MEWC is useful as an agentic browsing benchmark because it focuses on open-web interaction and multi-environment task execution rather than single-site scripted browsing.

BenchLM freshness & provenance

Version

MEWC 2026

Refresh cadence

Quarterly

Staleness state

Current

Question availability

Public benchmark set

CurrentDisplay only

BenchLM uses freshness metadata to decide whether a benchmark should still be treated as a strong differentiator, a benchmark to watch, or a display-only reference. For the full scoring policy, see the BenchLM methodology page.

FAQ

What does MEWC measure?

A benchmark that evaluates AI agents on multi-environment web challenges, testing navigation and task completion across diverse live web environments.

Which model scores highest on MEWC?

MiniMax M2.5 by MiniMax currently leads with a score of 74.4% on MEWC.

How many models are evaluated on MEWC?

1 AI models have been evaluated on MEWC on BenchLM.

Last updated: July 23, 2026 · BenchLM version MEWC 2026

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