Enterprise Environments

SnorkelLegal

Evaluates AI agents on whether they can advance a legal matter while preserving the chain from controlling evidence to procedure, authority, and action.

overview

SnorkelLegal evaluates agents within a simulated mid-market law firm, where every request is tied to a matter, a procedural stage, and a role with defined authority.

The release covers representative work across matter intake, conflicts, docketing, litigation holds, discovery, privilege, settlement authority, transactional exposure, and regulatory investigations. Agents must locate the correct matter and parties, find the controlling document or policy, distinguish current evidence from superseded material, and return a bounded legal work product or make a governed matter update.

The benchmark evaluates the intersection of long-context reasoning, matter-specific rules, and procedural discipline.

At a glance

200

frontier tasks

15

simulated personas represented

50%

semantic-output tasks

23.5%

tasks requiring state changes

Leaderboard

Rank Model Pass@1 Pass@5 Cost / Trial Cost / Task
1 Grok 4.6
40.7%
64.6%
$2.22 $11.12
2 GLM 5.3
37.8%
63.6%
$1.37 $6.83
3 Muse Spark 1.3
36.5%
55.5%
$1.45 $7.25
4 Kimi K3
36.1%
65.3%
$1.94 $9.69
5 Fable 5.1
35.9%
60.5%
$5.26 $26.31
6 DeepSeek V4 Pro
30.4%
63.5%
$1.37 $6.84
7 Claude Opus 5
26.4%
50%
$4.14 $20.69
8 Qwen 3.8 Max
25.6%
53.5%
$2.34 $11.69
9 Gemini Flash 3.8
25.3%
42%
$1.23 $6.16
10 GPT-6 Astra
20.9%
35.1%
$11.61 $58.04
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Frontier performance

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Methodology

Evaluator

Short exact answers and record changes are verified programmatically. Semantic legal work products are evaluated against scenario-specific rubrics for controlling rules, matter-specific facts, scope, and appropriate caveats. State, confidentiality and safety, process, and efficiency are measured separately.
timeout
The evaluation uses a fixed time and step budget for every run. Long-context tasks are therefore judged within a defined operating envelope rather than against unlimited retries. The release configuration should report the exact limits used.
integration

Each task runs inside a reproducible Docker/OpenEnv workspace with matter records, document evidence, role-gated MCP tools, and a simulated requester. The session preserves matter state and captures the complete trajectory, including retrieval, authority checks, user interaction, and governed writes. Seeded randomness supports repeatable failure-mode testing.

scoring note

Fluent legal prose is not enough. A task is incorrect when the agent relies on superseded evidence, skips a required authority or conflict check, makes an impermissible write, or gives a semantically wrong answer that merely sounds plausible. The score combines outcome gates with process and efficiency diagnostics while allowing valid alternative tool sequences.

Behind the benchmark

Legal work is not just retrieval plus prose. The operative rule may be firm-private or jurisdiction-specific. A matter file may place governing text next to superseded drafts and withdrawn analyses. Authority and confidentiality can determine whether an otherwise correct action is allowed.

SnorkelLegal turns those constraints into observable tests of grounding, sequencing, and restraint. The subset includes semantic legal outputs, long-context tasks, and governed matter updates. It asks a practical question for model developers: can an agent move a matter forward without inventing certainty, using the wrong version, or bypassing a control?

Tasks and rubrics are authored and reviewed by legal-domain experts.

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