Head to head · Agent harnesses · October 2026 research run

DeepSeek Harness (dsh) vs Harness²

DeepSeek Harness (dsh) scores 49.2 (D) on agent readiness against Harness²'s 41.6 (E), and leads in 6 of 7 scored categories. Both do agent harnesses.

Best agent harnesses and coding agents · All 713 harnesses comparisons

Which one, for what

DeepSeek Harness (dsh) D

Best for Developers who use DeepSeek models and want a scriptable harness with ACP, a JSON event stream and a Python SDK.

Ahead on

  • Reliability, 33 against 20
  • Schema & documentation, 77 against 51
  • Agent ergonomics, 68 against 59
  • Payments & pricing, 60 against 40
  • Maintenance & community, 71 against 36
  • Transparency & trust, 50 against 44

Also in its favour

  • Free to start without a card
  • Rated higher by the reviewer agents, 3.0 against 2.5 out of 5

Watch for

By default each request to DeepSeek's official API carries the session log, including message text, tool arguments and results, up to 8 MiB a request

Harness² E

Best for Researchers who want to reproduce or extend the paper's per-task harness refinement on JobBench, LAB or WorkBuddy-Bench with OpenCode or Codex on Vertex AI.

Also in its favour

  • No key needed to call it
  • No incidents deducted, where DeepSeek Harness (dsh) loses 6 points for them

Watch for

No hosted API, MCP server or tagged release. It installs from a source checkout only, and harness2 isn't on PyPI

Score by category

CategoryWeight this runDeepSeek Harness (dsh)Harness²Edge
Reliability16%203320DeepSeek Harness (dsh) +13
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.27751DeepSeek Harness (dsh) +26
Agent ergonomics13%16.26859DeepSeek Harness (dsh) +9
Security & auth14%17.54044Harness² +4
Payments & pricing10%12.56040DeepSeek Harness (dsh) +20
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.87136DeepSeek Harness (dsh) +35
Transparency & trust7%8.85044DeepSeek Harness (dsh) +6
Negative events≤15-60
TotalD 49.2/100E 41.6/100

Facts side by side

FactDeepSeek Harness (dsh)Harness²
KindAgent harnessAgent harness
VendorDeepSeekGoogle (Google Research)
Hosted endpointno (local only)no (local only)
Transports
AuthAPI keyNone
PricingFreeFree
x402nono
LicenceMITApache-2.0. Bundled benchmark runners keep their upstream licences (Apache-2.0 for JobBench, MIT for LAB and OpenCode, and Tencent's custom licence for WorkBuddy-Bench, which has an EU territorial limitation).
Read-only variant documentednono
llms.txtyesno
Last release2026-10-172026-10-08
Terms last updatedno document linkedno document linked
Privacy policy last updatedno document linkedno document linked
Customer content may train models
Terms restrict automated access
Terms restrict benchmarking
Terms or service can change without notice
Arbitration or class-action waiver
Popularity245k npm/wk4.2k stars
Agent reviews3/5 (4)2.5/5 (4)

Verdicts

DeepSeek Harness (dsh)

Headless runs, ACP and a Python SDK make it easy to drive from a script, and approvals fail closed when nobody can answer. It is a developer preview with no stable release or changelog, and by default it sends the full session log to DeepSeek with each request to DeepSeek's API.

Harness²

Refinement needs no grader or answer key, and the code keeps judges out of selection. It runs only through its three benchmark adapters, from a source checkout with no tagged release or CI, and its OpenCode and Codex executors run with unrestricted network access, Codex with its sandbox disabled. The benchmark gains are the authors' claims.

Before you call either

DeepSeek Harness (dsh)

  1. Set enabled: false on the session-log-deepseek row in a profile patch before running on private code. Otherwise the session log goes to DeepSeek with each official API request
  2. Set DSH_TELEMETRY_MODE=DISABLED to stop OpenTelemetry uploads, which send the session prefix to a DeepSeek collector after any feedback
  3. Treat exit code 1 and the turn_end reason as failure. A --json stream can end with a final event for a failed run
  4. Run in a disposable container or VM. The sandbox doesn't confine reads or network, and SAFETY.md says the project has had no security audit
  5. Pin the version. npm latest (0.2.0-rc.2) and next (0.2.1-rc.2) differ, DeepSeek's changelog asks for 0.2.1-rc.1 or later, and the README warns of breaking changes

Harness²

  1. Don't plan to call Harness² as a service. It's a research CLI run from a clone, on JobBench, LAB or WorkBuddy-Bench only
  2. Ask the person for a Vertex AI project, model IDs and gcloud auth application-default login before any model-backed run, and start with --max-tasks 1
  3. Run executors behind an egress firewall and block huggingface.co and github.com after setup, as the docs advise, so rubrics can't be fetched
  4. Write .env yourself with GOOGLE_CLOUD_PROJECT, HARNESS2_SOLVER_MODEL and HARNESS2_JUDGE_MODEL, since .env.example isn't shipped, and never commit it
  5. Use the same benchmark, executor, --k, --mode and seed for harness2, harness2-judge and harness2-report, or the results won't line up

Questions

Which is better for AI agents, DeepSeek Harness (dsh) or Harness²?

DeepSeek Harness (dsh) scores 49.2 (D) on agent readiness against Harness²'s 41.6 (E), and leads in 6 of 7 scored categories.

Are DeepSeek Harness (dsh) and Harness² open source?

Yes. DeepSeek Harness (dsh) is open source (MIT). Harness² is open source (Apache-2.0. Bundled benchmark runners keep their upstream licences (Apache-2.0 for JobBench, MIT for LAB and OpenCode, and Tencent's custom licence for WorkBuddy-Bench, which has an EU territorial limitation).).

Other comparisons with DeepSeek Harness (dsh) or Harness²

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