LLM Reference
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Toolathlon

Metric: Score (higher is better)Introduced: 2026

Tool-use benchmark reported in StepFun's Step 3.7 Flash launch materials.

Models ranked

4

tracked on this benchmark

Score band

78.4 – 48.2

best → lowest tracked

Snapshot trend

+30.20

Jun 13 → Aug 26 · 1 models

Leaderboard

Tracked models ranked by Score (higher is better).

Compare candidates
#Model variant and provenanceScore
1
GLM-5.3-Flash
Version: Toolathlon VerifiedHarness: Not recordedEvaluator: Not recordedObserved: Aug 26, 2026Confidence: Not recordedSource
78.4
2
Kimi K3
Version: Toolathlon-Verified; max reasoning effortHarness: Not recordedEvaluator: Not recordedObserved: Jul 16, 2026Confidence: Not recordedSource

Notes: Model variant: Kimi K3 (max reasoning effort). Benchmark variant: Toolathlon-Verified. Harness/evaluator not disclosed by Moonshot. Source posture: Moonshot/Kimi self-reported launch table; confidence: medium because the value is vendor-reported and not independently reproduced. Recommended seed value: 73.2.

73.2
3
Step 3.7 Flash
Version: Not recordedHarness: Not recordedEvaluator: Not recordedObserved: May 29, 2026Confidence: Not recordedSource
49.5
4
GLM-5.2
Version: Tool-Decathlon (% tasks completed)Harness: Not recordedEvaluator: Not recordedObserved: Jun 13, 2026Confidence: Not recordedSource
48.2

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.

Related benchmarks

Last reviewed: May 29, 2026

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