Vals EMB (EMB)
Evaluating agents on Excel-based financial modeling tasks
Data verifiedHow BenchLM shows EMB
BenchLM mirrors the public Vals AI EMB leaderboard captured from https://www.vals.ai/benchmarks/emb and updated by Vals on July 9, 2026. The snapshot preserves overall scores, uncertainty, latency, cost-per-test metadata, and task-level scores where Vals publishes them.
EMB 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.
EMB score on EMB — July 9, 2026
BenchLM mirrors the published emb score view for EMB. GPT-5.6 Sol leads the public snapshot at 72.34% , followed by Claude Opus 4.8 (69.37%) and GPT-5.6 Terra (67.61%). BenchLM does not use these results to rank models overall.
GPT-5.6 Sol
OpenAI
openai/gpt-5.6-sol
Claude Opus 4.8
Anthropic
anthropic/claude-opus-4-8
GPT-5.6 Terra
OpenAI
openai/gpt-5.6-terra
The published EMB snapshot is tightly clustered at the top: GPT-5.6 Sol sits at 72.34%, while the third row is only 4.72 points behind. The broader top-10 spread is 15.30 points, so the benchmark still separates strong models even when the leaders cluster.
20 models have been evaluated on EMB. The benchmark falls in the External benchmark mirrors category. BenchLM tracks this category separately from its weighted global scoring system, so these results are best compared on the dedicated Korean benchmark views. EMB is currently displayed for reference but excluded from the scoring formula, so it does not directly affect overall rankings.
About EMB
Year
2026
Tasks
Excel-based financial modeling tasks
Format
Accuracy score
Difficulty
Professional finance modeling
BenchLM mirrors the public Vals AI EMB 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.
BenchLM freshness & provenance
Version
EMB 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.
EMB score table (20 models)
FAQ
What does EMB measure?
Evaluating agents on Excel-based financial modeling tasks
Which model leads the published EMB snapshot?
GPT-5.6 Sol currently leads the published EMB snapshot with 72.34% emb score. BenchLM shows this benchmark for display only and does not use it in overall rankings.
How many models are evaluated on EMB?
20 AI models are included in BenchLM's mirrored EMB snapshot, based on the public leaderboard captured on July 9, 2026.
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