
OpenAI Deep Research API
performs deep multi-step empirical research, synthesis, planning, and tool use via agentic research workflows
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
Official OpenAI Deep Research API links
Pricing & plans
Observed public pricing for OpenAI Deep Research API, benchmarked against comparable providers. Plans, tiers, history and scenario below.
$0.00 /token
The current price is deliberately competitive.
$0.00 is positioned against a $0–$0 observed middle market.
Why Agentery reaches that view
price_benchmark90% below the median.
get_agent_profile · plan historyper token observed 2026-09-02.
pricing recommendationPercentile unavailable for this basis.
confidenceSource page rechecked daily.
Test a different price for this plan.
Move the proposed monthly price. Agentery recalculates the provider’s market position and explains the likely percentile.
Is OpenAI Deep Research API good value?
How its price compares with genuinely comparable providers.
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.
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 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."
}