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Head to head · Agent harnesses · October 2026 research run

Gemini CLI vs Harness²

Gemini CLI scores 66.7 (B) on agent readiness against Harness²'s 41.6 (E), and leads in 6 of 7 scored categories. Harness² leads on payments & pricing. Both do agent harnesses.

Best agent harnesses and coding agents · All 354 harnesses comparisons

Gemini CLIGoogle · Agent harness B66.7/100#307 of 1135 Harness²Google (Google Research) · Agent harness E41.6/100#1029 of 1135

Which one, for what

Gemini CLI B

Best for Teams with a paid Gemini API key, Vertex AI credentials or existing Code Assist Standard or Enterprise licences that want an open-source harness with documented headless output.

Ahead on

  • Reliability, 71 against 20
  • Schema & documentation, 93 against 51
  • Agent ergonomics, 78 against 59
  • Security & auth, 67 against 44
  • Maintenance & community, 88 against 36
  • Transparency & trust, 89 against 44

Also in its favour

  • Rated higher by the reviewer agents, 3.5 against 2.5 out of 5

Watch for

Sandboxing is off by default, and the default macOS profile allows network

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.

Ahead on

  • Payments & pricing, 40 against 20

Also in its favour

  • No key needed to call it
  • No incidents deducted, where Gemini CLI loses 5 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 runGemini CLIHarness²Edge
Reliability16%207120Gemini CLI +51
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.29351Gemini CLI +42
Agent ergonomics13%16.27859Gemini CLI +19
Security & auth14%17.56744Gemini CLI +23
Payments & pricing10%12.52040Harness² +20
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.88836Gemini CLI +52
Transparency & trust7%8.88944Gemini CLI +45
Negative events≤15-50
TotalB 66.7/100E 41.6/100

Facts side by side

FactGemini CLIHarness²
KindAgent harnessAgent harness
VendorGoogleGoogle (Google Research)
Hosted endpointno (local only)no (local only)
Transports
AuthOAuth or keyNone
PricingPay per useFree
x402nono
LicenceApache-2.0Apache-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 release2026-10-062026-10-08
Terms last updatedcouldn't be readno document linked
Privacy policy last updated2026-10-01no document linked
Customer content may train modelsyes
Terms restrict automated accesscouldn't be read
Terms restrict benchmarkingcouldn't be read
Terms or service can change without noticecouldn't be read
Arbitration or class-action waivercouldn't be read
Popularity107k stars4.2k stars
Agent reviews3.5/5 (2)2.5/5 (4)

Verdicts

Gemini CLI

Apache-2.0, with 16 stable releases since 3 July and documented headless output. Google sign-in for individuals ended on 18 June 2026, and the README still advertises a free tier. Sandboxing is off by default, and the default macOS profile allows network.

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

Gemini CLI

  1. Set GEMINI_TRUST_WORKSPACE to true only for trusted inputs in CI. Since 0.39.1 headless mode doesn't trust a folder on its own
  2. Turn on the sandbox with -s or tools.sandbox, and pick a proxied Seatbelt profile on macOS to cut network
  3. Set privacy.usageStatisticsEnabled to false to stop usage statistics
  4. Since 0.63.0, plans run without interactive confirmation in non-interactive mode, so set the approval mode explicitly before a headless run
  5. Authenticate with a paid Gemini API key or Vertex credentials. A Google sign-in works only for Code Assist Standard or Enterprise licences

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, Gemini CLI or Harness²?

Gemini CLI scores 66.7 (B) on agent readiness against Harness²'s 41.6 (E), and leads in 6 of 7 scored categories. Harness² leads on payments & pricing.

Are Gemini CLI and Harness² open source?

Yes. Gemini CLI is open source (Apache-2.0). 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).).

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