Skip to main content
BenchLM
Advertise

Benchmark profile

Vals SkillsBench (SkillsBench)

How important are skills for agents?

Data verified

How BenchLM shows SkillsBench

BenchLM mirrors the public Vals AI SkillsBench leaderboard captured from https://www.vals.ai/benchmarks/skillsbench and updated by Vals on June 24, 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.

13 Vals rows3 task viewspublic datasetTasks: Overall, No Skills, With SkillsDisplay only
SkillsBench on Vals AIVals methodologyVals home

SkillsBench score on SkillsBench — June 24, 2026

BenchLM mirrors the published skillsbench score view for SkillsBench. GPT-5.5 Codex leads the public snapshot at 62.55% , followed by GPT-5.5 (62.21%) and Claude Opus 4.8 (59.23%). BenchLM does not use these results to rank models overall.

1

GPT-5.5 Codex

OpenAI

openai/gpt-5.5-codex

62.55%
Overall —
2

GPT-5.5

OpenAI

openai/gpt-5.5

62.21%
Overall —
3

Claude Opus 4.8

Anthropic

anthropic/claude-opus-4-8

59.23%
Overall —
13 modelsExternal benchmark mirrorsCurrentDisplay onlyUpdated June 24, 2026

SkillsBench score table (13 models)

Score
1
GPT-5.5 CodexOpenAI
62.55%
2
GPT-5.5OpenAI
62.21%
3
Claude Opus 4.8Anthropic
59.23%
4
Qwen3.7 PlusAlibaba
54.30%
5
Gemini 3.5 FlashGoogle
52.74%
6
GPT-5.4OpenAI
51.71%
7
MiniMax M3MiniMax
51.50%
8
DeepSeek V4 ProDeepSeek
51.27%
9
Kimi K2.7 CodeMoonshot AI
50.04%
10
Claude Sonnet 4.6Anthropic
49.05%
11
GLM 5.2Zhipu AI
45.08%
12
Grok 4.3SpaceXAI
40.64%
13
InklingThinkingmachines
26.09%

The published SkillsBench snapshot places GPT-5.5 Codex first at 62.55%. The third row is 3.33 points behind. The broader top-10 range is 13.50 points, so the table still separates the published systems.

13 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.

SkillsBenchPublic benchmark source

BenchLM freshness & provenance

Version

SkillsBench 2026

Refresh cadence

Quarterly

Staleness state

Current

Question availability

Public benchmark set

CurrentDisplay only

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.

FAQ

What does SkillsBench measure?

How important are skills for agents?

Which model leads the published SkillsBench snapshot?

GPT-5.5 Codex currently leads the published SkillsBench snapshot with 62.55% skillsbench score. BenchLM shows this benchmark for display only and does not use it in overall rankings.

How many models are evaluated on SkillsBench?

13 AI models are included in BenchLM's mirrored SkillsBench snapshot, based on the public leaderboard captured on June 24, 2026.

Last updated: June 24, 2026 · mirrored from the public benchmark leaderboard

Choose a model with this week’s evidence

Join 2,000+ readers for ranking moves, pricing changes, and the claims that still need proof.

One email each week. Unsubscribe anytime.