DrumsBench

Research and benchmarks

Can many computer-use training attempts share one running computer without touching each other?

This is the public record of what Drums has tried, what broke, what was measured, and what has not been run yet. Nothing here is a claim of speed over anything until the matched numbers exist.

verified 4preliminary 7failed 9planned 7All records

Latest (2026-10-28): our first head-to-head benchmark, in plain language: where Drums wins, where it loses, and what is next.

The question

Training a computer-use agent by reinforcement learning needs thousands of isolated desktop environments, usually one virtual machine each. Every VM duplicates the operating system and the applications, which makes resets, checkpoints and scaling expensive. Drums is investigating a shared-runtime architecture: many attempts share one booted operating system and one set of initialised applications while keeping independent files, clipboard, display and input. The goal is more correctly verified training rollouts per dollar, faster resets, lower overhead, and isolation that holds for training correctness. This is an experimental thesis, not a proven improvement, and the evidence so far includes a pre-registered negative result and an unresolved restore failure.

one virtual machine per attemptdrums: one shared runtimestateappsOSkernelVM 1stateappsOSkernelVM 2…stateappsOSkernelVM Neach attempt boots a computer:N x (kernel + OS + apps + state)a VM reset restores a disk andmemory image (tens of seconds,gigabytes per attempt)ABCD…Nprivate state capsule per attemptone running OS+ initialized appsone runtime, N private states:(kernel + OS + apps) + N x statereset = swap the capsule state(copy-on-write; base untouched)scoped state, not a security boundary
The idea under test: one shared base runtime, private state per attempt. Not a system that exists.
Isolation and sharing pull against each other. Every experiment on this site is a measurement of where that line can sit without a reward being wrong.

The three experiments

  1. Runtime correctness and efficiency against tuned incumbents. Faithful checkpoint and restore, clean resets, isolation, memory per environment, and desktop throughput, compared with QEMU/KVM warm VM snapshots as the primary baseline, an OCI desktop with CRIU, the custom Drums runtime, and an OSGym or CUA-Sandbox style optimised implementation where it is reproducible and licensed. Equivalent apps, OS versions, tasks, checker, hardware allocation and reset semantics; every difference recorded.
  2. Real-agent rollout economics. Real multimodal agents on a frozen set of about 20 to 30 desktop tasks using genuine benchmark task definitions and external checkers where supported. Measured: completed and failed-but-valid trajectories, invalid or corrupted ones, task success, inference time and cost, environment time and cost, verification cost, recovery overhead.
  3. Actual RL with only the environment changed. Identical open-weight models, algorithm and rewards; only the runtime changes; a pre-registered target success rate; cost and time to reach it; multiple seeds; "never reached" reported honestly.

The third experiment cannot be interpreted until the first two pass. A learning-curve difference on a runtime whose restore is unfaithful or whose isolation is unmeasured is a difference in noise.

Targets exist (two times valid rollouts per hour, half the environment cost per rollout) and they are targets, not results. They were not chosen to be attractive, and the economic threshold that matters should be set by prospective customers, not chosen for a headline. Reset correctness of 100% and zero cross-rollout contamination are requirements, not targets.

Research status

As of 2026-10-25.

Verified (software evidence, not benchmark results)

Verified (harness validation, both arms Drums, not a comparison)

Preliminary

Failed

Planned

Current blockers

What is verified vs preliminary

ClaimStatusWhere
The macOS harness and its tests work on the target Macverified software evidenceEXP-001
Forking a shared server process saves 6.2% memory per session, not 15%measured, pre-registered negativeEXP-004
CRIU 4.3 drops a POSIX lock on a mapped file after restoreauthor-claimed probe in a sandbox; unresolvedEXP-009
runc always asks CRIU for an empty network namespaceread from source; live result author-claimedEXP-010
Any density, throughput, reset, isolation or cost number for any armnone existsbenchmarks
Drums is faster or cheaper than a VMnot claimed
from a run to a number on a pagerun on namedhardwareraw logs kept(never deleted)result folder+ meta.jsondata/results/*.json (schemacheck at build)pagegeneratedbuild fails on a row with no number, an unknown experiment id or a bad file name.a result file names its source paths; pages quote the file, never a typed number.status gates (never promoted; when in doubt, the lower one)verifiedmeasurement file on named hardware, run recordedpreliminaryreal; needs more runs, a positive control or an independent checkfailedran; missed a correctness, isolation, reset or pre-registered barplannedsource or protocol exists; nothing ran; no numbersrule: a contamination count of zero prints only next to a positive control that fired.
How a number reaches this site: raw logs in a results folder, a result file validated by schema at build, an experiment record that names hardware, commit and evidence paths, and only then a table. Author-claimed numbers without an artifact stop at the record and are quoted as claims.

How to read this site

Every record carries one of four statuses. verified: backed by measurement files we can point to, on named hardware, with the run recorded. preliminary: a real observation that needs more runs, a positive control or an independent check. failed: ran and missed a correctness, isolation, reset or pre-registered bar; kept on the record. planned: written as code or protocol, not executed, no numbers. When in doubt we use the lower status.

Every number carries a label the first time it appears: measured, author-reported (a paper), author-claimed (text with no artifact), vendor claim, design value, or estimate.