Vals SkillsBench (SkillsBench)
We mirror this table; we do not rank on it.
How important are skills for agents?
SkillsBench score on SkillsBench — September 11, 2026
We mirror the published skillsbench score view for SkillsBench. DeepSeek V4.1 Flash leads the public snapshot at 69.80%, followed by Grok 4.5 (66.03%) and Gemini 3.7 Flash (65.89%). We do not use these results to rank models overall.
DeepSeek V4.1 Flash
DeepSeek
OpenHands · high reasoning
OpenHands
Grok 4.5
xAI
OpenHands · high reasoning
OpenHands
Gemini 3.7 Flash
OpenHands · high reasoning
OpenHands
35 modelsExternal benchmark mirrorsCurrentDisplay onlyUpdated September 11, 2026
SkillsBench score table (35 models)
ScoreHow SkillsBench is shown here
BenchLM mirrors the public Vals AI SkillsBench leaderboard captured from https://www.vals.ai/benchmarks/skillsbench and updated by Vals on September 11, 2026. The snapshot preserves overall scores, uncertainty, latency, cost-per-test metadata, and task-level scores where Vals publishes them.
SkillsBench is display only on BenchLM. Vals proprietary or Vals-hosted aggregate views are useful context, but BenchLM does not use them as weighted ranking inputs or as a replacement for benchmark-native source records.
Snapshot
The published SkillsBench snapshot places DeepSeek V4.1 Flash first at 69.80%. The third row is 3.91 points behind. The broader top-10 range is 10.61 points, so the table still separates the published systems.
35 models have been evaluated on SkillsBench. The benchmark falls in the External benchmark mirrors category. We keep external benchmark mirrors separate from the weighted global scoring system, so these results remain source-specific evidence. SkillsBench is currently displayed for reference but excluded from the scoring formula, so it does not directly affect overall rankings.
About SkillsBench
Year
2026
Tasks
Agent skill-importance tasks
Format
Accuracy score
Difficulty
Agent skill evaluation
BenchLM mirrors the public Vals AI SkillsBench leaderboard as display-only external evidence. The captured snapshot preserves overall scores, task-level scores where Vals publishes them, uncertainty, latency, and cost-per-test metadata. It is excluded from BenchLM weighted rankings.
Freshness and provenance
Version
SkillsBench 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.
Questions
What does SkillsBench measure?
How important are skills for agents?
Which model leads the published SkillsBench snapshot?
DeepSeek V4.1 Flash currently leads the published SkillsBench snapshot with 69.80% skillsbench score. BenchLM shows this benchmark for display only and does not use it in overall rankings.
How many models are evaluated on SkillsBench?
The September 11, 2026 snapshot contains 35 AI models.
Know when it’s worth switching models
The model to choose, the cheaper alternative, and the release we would wait on.
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