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Deepresearch Bench Ii

↗ agentresearchlab.com/benchmarks/deepresearch-bench-ii/index.html official website

Evaluates and diagnoses deep research AI agents using fine-grained rubrics derived from expert-authored research reports

infrastructure
Agentery price verdictNo pricing observed
Billing model—
Last observation13 Oct 2026pricing pages rechecked daily
Website liveness13 Oct 2026alive · separate from pricing

What it does

The specific capability behind this listing, and where to get it.

Deepresearch Bench Ii

Evaluates and diagnoses deep research AI agents using fine-grained rubrics derived from expert-authored research reports

Deep research tasks and system-generated research reports (132 research tasks derived from expert reports) → Rubric-based evaluations and leaderboard scores across Information Recall, Analysis, and Presentation dimensions
MCPautonomy: infrastructure
Price status · observed daily

No public commercial pricing observed.

No price does not imply the product is free. Any code-host platform pricing is excluded.

Is Deepresearch Bench Ii good value?

Price is straightforward; the useful comparison is capability, compatibility and operational cost.

No price benchmark

No public commercial pricing observed.

Agentery has not observed a public price for this provider. No price does not mean free.

Observed commercial pricenone
NicheAgent Observability Eval
Price benchmarknot applicable
What to compare instead

Check capability before deciding

Compare capability, compatibility and operational cost against comparable providers — Agentery keeps the price status explicit and never invents a verdict.

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Deepresearch Bench Ii's local market

Nearest products by what they do — a different cohort from the buyer-tier benchmark above.

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See the MCP response behind this page · get_provider_profile()
See the MCP response behind this pageget_provider_profile (get_agent_profile remains a callable alias)
{
  "agent_id": "deepresearch_bench_ii",
  "name": "Deepresearch Bench Ii",
  "url": "https://agentresearchlab.com/benchmarks/deepresearch-bench-ii/index.html",
  "logo": null,
  "niche": "agent-observability-eval",
  "category": "developer-tools-infra",
  "short_summary": "Evaluates and diagnoses deep research AI agents using fine-grained rubrics derived from expert-authored research reports",
  "task_performed": "Evaluates and diagnoses deep research AI agents using fine-grained rubrics derived from expert-authored research reports",
  "inputs_accepted": [
    "Deep research tasks and system-generated research reports (132 research tasks derived from expert reports)"
  ],
  "outputs_produced": [
    "Rubric-based evaluations and leaderboard scores across Information Recall",
    "Analysis",
    "and Presentation dimensions"
  ],
  "integrations_available": [],
  "protocols_or_interfaces": [
    "MCP"
  ],
  "industry_fit": [
    "AI agent research and development"
  ],
  "autonomy_level": "infrastructure",
  "human_approval_needed": "unclear",
  "pricing_model": "unclear",
  "price": {
    "observed": false,
    "billing": "not_found",
    "currency": null,
    "lowest_monthly_usd": null,
    "monthly_usd": null,
    "headline": "No public price found",
    "summary": "No public price found on the vendor site.",
    "confidence": "high",
    "source_url": "https://agentresearchlab.com/benchmarks/deepresearch-bench-ii/index.html",
    "checked_at": "2026-10-12T01:32:44.134Z",
    "source_kind": "vendor",
    "amount": null,
    "display": null,
    "plans": [],
    "source": "render+llm"
  },
  "trust_or_rating_signal": [
    "Academic paper / arXiv preprint",
    "University of Science and Technology of China affiliation",
    "300+ expert hours for review",
    "9,430 verifiable rubrics",
    "Code repository (GitHub)"
  ],
  "evidence_quality": "medium",
  "entity_type": "infrastructure",
  "regulated_data_suitability": "unclear",
  "evidence_urls": [
    "https://agentresearchlab.com/benchmarks/deepresearch-bench-ii/index.html",
    "https://github.com/NVIDIA-AI-Blueprints/aiq-research-assistant",
    "https://agentresearchlab.com/benchmarks/deepresearch-bench-ii/index.html#leaderboard"
  ],
  "last_checked": "2026-06-16",
  "how_to_connect": {
    "website": "https://agentresearchlab.com/benchmarks/deepresearch-bench-ii/index.html",
    "docs": "https://github.com/documentation",
    "mcp": null,
    "a2a": null,
    "api": {
      "docs_url": "https://github.com/developer",
      "endpoint": null
    },
    "protocols": [
      "MCP"
    ],
    "install": null,
    "repository": null,
    "note": "Speaks MCP but publishes no endpoint we could verify — check the docs/website."
  },
  "deployment": {
    "model": "unknown",
    "both_offered": false,
    "hosted_endpoint": null,
    "install": null,
    "note": "No deployment evidence held — Agentery has no endpoint, install instruction or directory attribute for this listing.",
    "evidence": null
  },
  "licence": {
    "name": null,
    "note": "No named licence found in the retained page text or source attributes. A public repository alone does not establish an open-source licence.",
    "evidence": null
  },
  "evidence_checks": {
    "price": {
      "status": "unknown",
      "note": "no observed price page text held for this listing"
    },
    "agent_card": {
      "status": "unknown",
      "note": "no Agent Card URL recorded for this listing"
    },
    "endpoint": {
      "status": "unknown",
      "note": "endpoint not yet checked"
    }
  },
  "product_group": null,
  "liveness": {
    "probed": true,
    "alive": true,
    "endpoint_kind": "site",
    "latency_ms": 912,
    "uptime_7d": 0.88,
    "checked_at": "2026-10-13T02:35:17.030Z",
    "consecutive_failures": 0,
    "status": "alive"
  },
  "price_extras": {
    "free_tier": null,
    "unit_cost": null
  },
  "reported_success": null,
  "feedback": "If you actually use this provider, call report_outcome with the result. Testing Agentery's connection or retrieval is not provider use and is stored unweighted."
}