activeMultimodalTool use

BabyVision w/ tools

Metric: Pass@1 (higher is better)Introduced: 2026

Visual reasoning benchmark evaluated with tool access. DeepSeek V4.1 Flash launch materials use the Claude Code harness with a 512k-token context window.

Models ranked

5

tracked on this benchmark

Score band

95.4 – 80.2

best → lowest tracked

Snapshot trend

+2.90

Oct 17 → Oct 23 · 1 models

Leaderboard

Tracked models ranked by Pass@1 (higher is better).

Compare candidates
#Model variant and provenanceScore
1
Version: BabyVision w/ python; four-run mean; max reasoning effortHarness: Not recordedEvaluator: Not recordedObserved: Oct 23, 2026Confidence: Not recordedSource

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

95.4
2
Version: BabyVision w/ toolsHarness: Not recordedEvaluator: Not recordedObserved: Oct 17, 2026Confidence: Not recordedSource
92.5
3

Configuration: MiniMax M3.1 Flash

Version: BabyVision (w/ tools)Harness: Claude Code 2.1.285 (min image side 1,500px)Evaluator: MiniMaxObserved: Oct 19, 2026Confidence: self-reportedSource

Notes: MiniMax M3.1 Flash launch blog (2026-10-19) main benchmark table image m31-flash-en-2 (webp converted to png; values transcribed by eye from table) incl. footnotes. Retrieved 2026-10-19.

91.0
4
Version: BabyVision w/ tools Pass@1; Claude Code harness; 512k contextHarness: Not recordedEvaluator: Not recordedObserved: Sep 10, 2026Confidence: Not recordedSource
89.6
5
Version: BabyVision (w/ tools); xhigh reasoning effortHarness: Not recordedEvaluator: Not recordedObserved: Oct 15, 2026Confidence: Not recordedSource

Notes: Meta HF model card Benchmarks table, xhigh reasoning effort.

80.2

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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