DataSpace: leaderboard
DataSpace (Li et al., 2026) asks a data agent to answer analytics questions over task-local workspaces that mix databases, CSV and JSON files, long documents and videos, returning the complete result table. A task counts as solved only when a deterministic evaluator matches the returned table to the gold table after header-invariant column alignment and type- and precision-aware normalization; the score is the percentage of 410 tasks solved, higher is better. Rows use the DataSpace-Agent reference harness unless the label names another agent harness.
Metric: Task accuracy (%; share of the 410 DataSpace tasks, each a question over a task-local heterogeneous workspace of CSV, JSON, SQLite, Markdown, PDF and video artifacts, whose returned table matches the gold table under the deterministic evaluator: header-invariant column alignment, type- and precision-aware normalization and order-aware row comparison; DataSpace-Agent reference harness unless the row names another harness). Source: arxiv.org. Saturation forecast: Around February 2027. 10 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Grok 4.5 | 66.34 | #82 |
| 2 | GPT-5.6 Sol | 64.63 | #30 |
| 3 | Kimi K3 | 53.41 | #54 |
| 4 | MiMo-V2.5 | 39.27 | #354 |
| 5 | Claude Sonnet 5 | 32.93 | #111 |
| 6 | MiniMax-M3 | 28.54 | #269 |
No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.
Interactive version: theaggregate.ai/benchmark?slug=dataspace · How It Works · Data refreshed daily, snapshot 2026-11-13.