Agentery pricing intelligence · Provider profile · OpenAI Deep Research API
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OpenAI Deep Research API

developers.openai.com/cookbook/examples/deep_research_api/introduction_to_deep_research_api_agents official website

performs deep multi-step empirical research, synthesis, planning, and tool use via agentic research workflows

infrastructurePricing checked daily
Agentery value verdictBelow the niche medianfrom $0/mo
Observed entry price$0/molowest observed monthly
Billing modelunclear
Last checked2 Sept 2026pricing & liveness

What it does

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

OpenAI Deep Research API

performs deep multi-step empirical research, synthesis, planning, and tool use via agentic research workflows

user research queries/prompts, web search results, internal files via MCP → research reports with citations, streamed research progress, structured outputs (tables, headers)
OpenAI Agents SDKOpenAI APIWebSearchToolMCPGitHubSDKAPIMCPautonomy: agentic

Pricing & plans

Observed public pricing for OpenAI Deep Research API, benchmarked against comparable providers. Plans, tiers, history and scenario below.

Pricing · observed daily
per token · market position

$0.00 /token

90% below the median. Cheaper than 1 of 1 comparable providers.
this agent · $0.00
$0median $0.00$0
observed 2026-09-02 · rechecked daily · source evidence retained
What should this agent charge?

The current price is deliberately competitive.

pricing recommendation
$0.00
$0$0
$0.00

$0.00 is positioned against a $0–$0 observed middle market.

Pricing checks returned

Why Agentery reaches that view

price_benchmark

90% below the median.

get_agent_profile · plan history

per token observed 2026-09-02.

pricing recommendation

Percentile unavailable for this basis.

confidence

Source page rechecked daily.

Interactive provider scenario

Test a different price for this plan.

Move the proposed monthly price. Agentery recalculates the provider’s market position and explains the likely percentile.

$2e-7 / month
$1 lowestmedian $0.00$0 highest
Competitive value position. At $2e-7/month, this plan is 90% below the niche median.
1st
-90%
$0$0

Is OpenAI Deep Research API good value?

How its price compares with genuinely comparable providers.

Below the niche median

Below the niche median for its buyer tier.

Benchmarked against comparable providers at the same buyer tier and billing unit — the entry plan sits 90% below the observed median.

Observed commercial price$2e-7/mo
NicheDeep Research Agent
Price benchmarkapplicable
How it compares

Compared with Deep Research Agent

Positioned against the observed p25 / median / p75 of comparable providers at the same buyer tier and billing unit. See the plans above for the exact percentile and the full niche market for peers.

View the full niche →

OpenAI Deep Research API's local market

Nearest products by what they do.

See the full market →
See the MCP response behind this page · get_agent_profile()
See the MCP response behind this pageget_agent_profile
{
  "agent_id": "openai_deep_research",
  "name": "OpenAI Deep Research API",
  "url": "https://developers.openai.com/cookbook/examples/deep_research_api/introduction_to_deep_research_api_agents",
  "logo": "https://agentery.com/logos/CP-HS5SNE-ld256.png",
  "niche": "deep-research-agent",
  "category": "research-knowledge-work",
  "short_summary": "performs deep multi-step empirical research, synthesis, planning, and tool use via agentic research workflows",
  "task_performed": "performs deep multi-step empirical research, synthesis, planning, and tool use via agentic research workflows",
  "inputs_accepted": [
    "user research queries/prompts",
    "web search results",
    "internal files via MCP"
  ],
  "outputs_produced": [
    "research reports with citations",
    "streamed research progress",
    "structured outputs (tables",
    "headers)"
  ],
  "integrations_available": [
    "OpenAI Agents SDK",
    "OpenAI API",
    "WebSearchTool",
    "MCP",
    "GitHub"
  ],
  "protocols_or_interfaces": [
    "SDK",
    "API",
    "MCP"
  ],
  "industry_fit": [
    "general business",
    "developer tools",
    "research"
  ],
  "autonomy_level": "agentic",
  "human_approval_needed": "unclear",
  "pricing_model": "unclear",
  "price": {
    "observed": true,
    "billing": "usage",
    "currency": "USD",
    "lowest_monthly_usd": null,
    "monthly_usd": null,
    "headline": "Paid (price not published)",
    "summary": "OpenAI API pricing is usage-based, with the documented deep-research example using gpt-5.6-terra at $2.00 per 1M standard input tokens and $12.00 per 1M standard output tokens.",
    "confidence": "high",
    "source_url": "https://developers.openai.com/api/docs/pricing",
    "checked_at": "2026-09-02T05:02:19.855Z",
    "amount": null,
    "display": null,
    "plans": [
      {
        "name": "gpt-5.6-sol",
        "price": "$5.00 per 1M input tokens",
        "usage": true,
        "period": "usage",
        "persona": "individual",
        "highlights": [
          "Standard input: $5.00 per 1M tokens",
          "Standard cached input: $0.50 per 1M tokens",
          "Standard cache writes: $6.25 per 1M tokens",
          "Standard output: $30.00 per 1M tokens",
          "Fast mode input: $10.00 per 1M tokens",
          "Fast mode output: $45.00 per 1M tokens"
        ],
        "price_annual": null
      },
      {
        "name": "gpt-5.6-terra",
        "price": "$2.00 per 1M input tokens",
        "usage": true,
        "period": "usage",
        "persona": "individual",
        "highlights": [
          "Standard input: $2.00 per 1M tokens",
          "Standard cached input: $0.20 per 1M tokens",
          "Standard cache writes: $2.50 per 1M tokens",
          "Standard output: $12.00 per 1M tokens",
          "Fast mode input: $4.00 per 1M tokens",
          "Fast mode output: $18.00 per 1M tokens"
        ],
        "price_annual": null
      },
      {
        "name": "gpt-5.6-luna",
        "price": "$0.20 per 1M input tokens",
        "usage": true,
        "period": "usage",
        "persona": "individual",
        "highlights": [
          "Standard input: $0.20 per 1M tokens",
          "Standard cached input: $0.02 per 1M tokens",
          "Standard cache writes: $0.25 per 1M tokens",
          "Standard output: $1.20 per 1M tokens",
          "Fast mode input: $0.40 per 1M tokens",
          "Fast mode output: $1.80 per 1M tokens"
        ],
        "price_annual": null
      },
      {
        "name": "gpt-image-2",
        "price": "$8.00 per 1M image input tokens",
        "usage": true,
        "period": "usage",
        "persona": "individual",
        "highlights": [
          "Image input: $8.00 per 1M tokens",
          "Image cached input: $2.00 per 1M tokens",
          "Image output: $30.00 per 1M tokens",
          "Text input: $5.00 per 1M tokens",
          "Text cached input: $1.25 per 1M tokens"
        ],
        "price_annual": null
      }
    ],
    "source": "render+llm"
  },
  "trust_or_rating_signal": [
    "Zero Data Retention support for Enterprises"
  ],
  "evidence_quality": "high",
  "entity_type": "infrastructure",
  "regulated_data_suitability": "Zero Data Retention stated for Enterprises",
  "evidence_urls": [
    "https://developers.openai.com/cookbook/examples/deep_research_api/introduction_to_deep_research_api_agents"
  ],
  "last_checked": "2026-06-16",
  "how_to_connect": {
    "website": "https://developers.openai.com/cookbook/examples/deep_research_api/introduction_to_deep_research_api_agents",
    "docs": "https://developers.openai.com/docs",
    "mcp": null,
    "a2a": null,
    "api": {
      "docs_url": "https://developers.openai.com/api",
      "endpoint": null
    },
    "protocols": []
  },
  "liveness": {
    "probed": true,
    "alive": true,
    "endpoint_kind": "site",
    "latency_ms": 965,
    "uptime_7d": 1,
    "checked_at": "2026-09-02T02:39:27.945Z",
    "consecutive_failures": 0,
    "status": "alive"
  },
  "price_extras": {
    "free_tier": null,
    "unit_cost": null
  },
  "reported_success": null,
  "feedback": "If you use this listing, call report_outcome afterwards — it sharpens rankings for everyone including you."
}