Benchmarks & Comparisons

How SWE-Enterprise stacks up against the most widely used AI evaluation benchmarks — and why enterprise context matters.

Comparison Matrix

SWE-Enterprise is the only dataset that combines enterprise context, multi-file reasoning, bug injection, and RAG evaluation in one package.

Dimension	SWE-Enterprise	SWE-bench	HumanEval	ServiceNow	AgentBench
Total Tasks	97,290	2,294	164	9,228	1,355
Enterprise Context	Code + Slack + ADRs + Metadata			Task prompts only	Limited environments
Multi-File Reasoning	3+ files per mission	Single file	Single function	Single task	Some multi-step
Bug Injection	1–3 deliberate bugs per world	Real bugs	Synthetic only	No bugs	No bugs
RAG Evaluation	Retrieval + Reasoning + Grounding
Domain Coverage	10 enterprise domains	Python only	Python only	ITSM only	8 diverse tasks
Commercial License	Full training & deployment	Open source	Open source	Apache 2.0	MIT
Data Format	Directory + JSONL + RAG bundles	JSON	Python tests	JSON tasks	JSON configs

Why It Matters

Single-file coding isn't real engineering

SWE-bench and HumanEval test isolated code changes in single files. But enterprise engineering requires understanding cross-service dependencies, reading Slack context, consulting ADRs, and debugging in unfamiliar codebases. SWE-Enterprise is the only benchmark that simulates this reality.

RAG pipelines need structured evaluation

Most RAG benchmarks test retrieval against Wikipedia passages. Enterprise RAG requires retrieving relevant code from a Slack mention, reasoning across multiple documents, and grounding answers in architecture decisions. SWE-Enterprise provides all three task types out of the box.

Agentic workflows demand multi-step validation

Current benchmarks measure whether a model produces the right output. They don't test whether it can diagnose an issue from a Slack report, locate the relevant code, plan a fix, and validate it against existing architecture. SWE-Enterprise missions require this end-to-end reasoning.

Domain diversity prevents overfitting

Models trained on single-domain benchmarks (Python-only, ITSM-only) overfit to those patterns. SWE-Enterprise spans 10 enterprise domains with distinct code patterns, terminology, and architecture styles — forcing models to generalize rather than memorize.

Getting Started

Download a free sample world to explore the structure
Choose an edition that matches your scale
Load worlds into your training pipeline or RAG system
Use the built-in RAG task splits for evaluation
Cite SWE-Enterprise in your publications

Download Free Sample →

See the full documentation for detailed setup instructions and API reference.

Editions

From free samples to enterprise-wide deployment. All editions include full Commercial Training License.

Feature	Evaluation	Research	Professional	Enterprise
5 Preview Worlds	✓	✓	✓	✓
1,000 Worlds	—	✓	✓	✓
5,000 Worlds	—	—	✓	✓
Full 24,316 Worlds	—	—	—	✓
Commercial License	—	✓	✓	✓
QA Report	✓	✓	✓	✓
Dataset Updates	—	6 months	12 months	Ongoing
Priority Support	—	—	✓	✓

Evaluation

5 worlds · Evaluate quality before you commit.

5 enterprise worlds
Sample from all 10 domains
All 5 components per world
Unrestricted evaluation

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Research

1,000 worlds · For individuals, universities, and startups.

1,000 enterprise worlds
All 10 domains represented
1,000+ RAG evaluation tasks
Full commercial training license
Documentation bundle

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Professional

5,000 worlds · Built for commercial AI teams.

5,000 enterprise worlds
Stratified domain sampling
20,000+ RAG evaluation tasks
Full commercial training license
Priority support

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Enterprise

Full dataset · For organizations requiring maximum coverage.

24,316 worlds (full dataset)
Maximized domain + difficulty coverage
97,290 RAG evaluation tasks
Full commercial training license
Custom domain weighting available
Dedicated support + onboarding

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