A Model Context Protocol task benchmark used in Qwen's launch tables to measure practical execution over MCP-style tools and integrations.
BenchLM mirrors the published score view for MCP-Tasks. Qwen3.5 397B leads the public snapshot at 74.2% , followed by Qwen3.6 Plus (74.1%) and Claude Opus 4.5 (71.8%). BenchLM does not use these results to rank models overall.
Qwen3.5 397B
Alibaba
Qwen3.6 Plus
Alibaba
Claude Opus 4.5
Anthropic
The published MCP-Tasks snapshot is tightly clustered at the top: Qwen3.5 397B sits at 74.2%, while the third row is only 2.4 points behind. The broader top-10 spread is 15.1 points, so the benchmark still separates strong models even when the leaders cluster.
5 models have been evaluated on MCP-Tasks. The benchmark falls in the Agentic category. This category carries a 22% weight in BenchLM.ai's overall scoring system. MCP-Tasks is currently displayed for reference but excluded from the scoring formula, so it does not directly affect overall rankings.
Year
2026
Tasks
MCP-integrated tool tasks
Format
Interactive tool-use evaluation
Difficulty
Advanced MCP workflows
MCP-Tasks is distinct from MCP Atlas in the Qwen3.6 comparisons. BenchLM keeps it separate until a fuller public benchmark specification is available because it appears to represent a different task protocol and score scale.
Version
MCP-Tasks 2026
Refresh cadence
Quarterly
Staleness state
Current
Question availability
Public benchmark set
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.
A Model Context Protocol task benchmark used in Qwen's launch tables to measure practical execution over MCP-style tools and integrations.
Qwen3.5 397B by Alibaba currently leads with a score of 74.2% on MCP-Tasks.
5 AI models have been evaluated on MCP-Tasks on BenchLM.
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