Catalog Systems Memory benchmarks & evaluation OSWorld

OSWorld

https://os-world.github.io/

HKU NLP + Salesforce's OSWorld — full-desktop agent benchmark with 369 tasks spanning real applications (LibreOffice, GIMP, Chrome, VS Code, Thunderbird, Files) across Ubuntu, Windows, and macOS. Tasks require multi-application workflows; evaluation via post-task state inspection (not just screenshot match). Released NeurIPS 2024.

Active · Verified 2026-10-28 · fresh as of 2026-10-28 · 29 cited facts, 0 with a third-party source · Suggest a correction

At a glance

Type
Desktop OS agent benchmark — 369 tasks across Ubuntu / Windows / macOS vendor fix
Tier
T3
Section
Memory benchmarks & evaluation
Created
2024-04 (Xie et al. arXiv 2404.07972) vendor fix
Latest release
not applicable — not OSS fix
License
Apache-2.0 vendor fix
GitHub
1.7k★ Python vendor fix
Pricing
not applicable — open benchmark; free to use vendor fix
Funding
not applicable — not commercial fix
Freshness
2026-10-28 fix
Layer
agent-infra repo fix
Licensing
open-source vendor fix

Memory taxonomy

storage
n/a
retrieval
n/a
persistence
n/a
update
read-only
unit
n/a
governance
n/a
conflict
n/a

When to use

Optimised for: not applicable - eval dataset, not a system

Anti-fit: not applicable - eval dataset, not a system

Pros & cons

Pros

Multi-OS (Linux + Windows + macOS) coverage unique among OS benchmarks; real apps; state-based evaluation more robust than screenshot match.

Cons

VM setup is heavyweight (gigabytes); SOTA still ~22% — long horizon to human parity; OSWorld game tasks (per spec) are not the focus — productivity apps dominate.

Claims & capabilities

NeurIPS 2024; 369 real-OS tasks across 3 operating systems; SOTA (Claude 3.5 Sonnet + Anthropic Computer Use) ~22% success

Technical surface

API surface
not applicable — eval dataset, not a system
Backend storage
not applicable — eval dataset, not a system
Deployment
not applicable — run locally
Embedding model
not applicable — eval dataset, not a system
Multi-tenancy
not applicable — eval dataset, not a system
MCP
not applicable — benchmark / evaluation harness
A2A
not applicable — benchmark / evaluation harness
OpenTelemetry
not applicable — benchmark / evaluation harness

Similar systems

Other memory benchmarks & evaluation in the catalog, ranked by inbound references.

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  • GAIA T3

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  • LongBench T3

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  • LongMemEval T3

    5 core memory abilities — info extraction, multi-session reasoning, temporal reasoning, knowledge updates, abstention — via 500 curated questions in synthetic chat histories. Two scales: LongMemEval-S (115K tokens), LongMemEval-M (up to 1.5M).

  • RULER T3

    NVIDIA. Extends NIAH with multi-needle retrieval, multi-hop entity tracing, aggregation, QA — configurable for arbitrary length / difficulty. Evaluated 17 long-context models on 13 tasks.

  • InfiniteBench (∞Bench) T3

    Tsinghua / OpenBMB. First benchmark with average input >100K tokens. 12 tasks across English + Chinese: long novel QA, code debugging, math in long context, summarisation, retrieval. Realistic documents (novels, code) rather than synthetic filler.

Sources (28 cited facts, 0 third-party)

Each fact links to the page it came from; the badge says who published it (how to read sources).