activeMultimodalTool use

ZeroBench-main w/ tools

Metric: Pass@5 (higher is better)Introduced: 2026

ZeroBench main split evaluated with tool access. DeepSeek V4.1 Flash launch materials report Pass@5 with the Claude Code harness and a 512k-token context window.

Models ranked

2

tracked on this benchmark

Score band

63.0 – 49.0

best → lowest tracked

Snapshot trend

+14.00

Sep 10 → Oct 23 · 1 models

Leaderboard

Tracked models ranked by Pass@5 (higher is better).

Compare candidates
#Model variant and provenanceScore
1
Version: ZeroBench-main w/ python Pass@5; max reasoning effortHarness: Not recordedEvaluator: Not recordedObserved: Oct 23, 2026Confidence: Not recordedSource

Notes: Moonshot self-reported launch table, row 'ZeroBench_main w/ python (pass@5)', column 'Kimi K3.1 Pro (max)'. Settings: reasoning effort max, temperature 1.0, top-p 0.95 (blog footnote).

63.0
2
Version: ZeroBench-main w/ tools Pass@5; Claude Code harness; 512k contextHarness: Not recordedEvaluator: Not recordedObserved: Sep 10, 2026Confidence: Not recordedSource
49.0

How to read this benchmark

This benchmark scores models where higher is better. Use scores for directional filtering and shortlisting, not universal quality ranking; then validate pricing, context window, provider availability, and fit for your workload.

Trust this score when

  • There is a fresh timestamped snapshot (or multiple snapshots) for this benchmark.
  • The model list covers the same version family you can actually deploy today.
  • Top candidates overlap with your required routing and feature requirements.

Be cautious when

  • There is only one benchmark snapshot or the dataset appears stale.
  • The benchmark metric direction is opposite of your decision objective.
  • The score difference between options is narrow and likely within implementation variance.

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Last reviewed: Sep 10, 2026

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