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Documentation Index

Fetch the complete documentation index at: https://docs.perplexity.ai/llms.txt

Use this file to discover all available pages before exploring further.

​
Overview

finance_search lets the model pull structured financial and market data for public companies, ETFs, and related instruments. The model decides which fields to fetch based on your prompt. Use it when one answer needs more than one type of financial data, such as valuation, earnings, and context for the same company or list of companies.

​
Capabilities

Data areaWhat it includes
Company basicsQuotes, profiles, peers, and market metadata
FinancialsIncome statement, balance sheet, cash flow (quarterly and annual), key ratios
Valuation and pricingCurrent/near-real-time pricing, 1-minute to 1-month OHLCV ranges, pre-market and after-hours data
EarningsLast earnings call transcript, report filings, beat/miss history, guidance discussion
Segment and KPI trackingRevenue/profit by segment, geography, ARPU, subscriber counts, GMV, and other operating metrics
Analyst coverageForward revenue and EPS estimates, cover count, historical estimate changes
Market activityTop gainers, top losers, and most active symbols
Ownership and corporate actionsInsider activity, ticker-level metadata, splits, and related market events
ETF and index detailsTop constituents, shares, weights, and market values

​
Quickstart

Add finance_search to the tools array. 
from perplexity import Perplexity

client = Perplexity()

response = client.responses.create(
    model="perplexity/sonar",
    input="What's NVIDIA trading at right now, and what is its current P/E?",
    tools=[{"type": "finance_search"}]
)

print(response.output_text)

{
  "background": false,
  "completed_at": 1777644610,
  "created_at": 1777644610,
  "error": null,
  "frequency_penalty": 0,
  "id": "resp_d0476d0f-872d-492a-907e-1daa48eb9e32",
  "incomplete_details": null,
  "instructions": null,
  "max_output_tokens": 8192,
  "max_tool_calls": null,
  "metadata": {},
  "model": "perplexity/sonar",
  "object": "response",
  "output": [
    {
      "categories": ["quote"],
      "results": [
        {
          "category": "quote",
          "content": "## NVDA Quote\nQuote field guide: `price` is the latest quote/current price...\n| symbol | name | timestamp | market_status | price | currency | change | changesPercentage | marketCap | pe | eps | volume | dayLow | dayHigh | yearLow | yearHigh | previousClose | open |\n| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |\n| NVDA | NVIDIA Corporation | 2026-05-01 14:10:07 UTC | open | 200.23 | USD | 0.66 | 0.33 | 4,866,492,706,948 | 40.86 | 4.90 | 28,725,330 | 199.15 | 203 | 110.82 | 216.83 | 199.57 | 201.28 |",
          "sources": [
            "https://www.perplexity.ai/finance/NVDA/historical-data",
            "https://www.perplexity.ai/finance/NVDA"
          ],
          "tickers": ["NVDA"]
        }
      ],
      "tickers": ["NVDA"],
      "type": "finance_results"
    },
    {
      "content": [
        {
          "annotations": [],
          "logprobs": [],
          "text": "NVIDIA (NVDA) is currently trading at **$200.23** per share, and its current P/E ratio is **40.86**.",
          "type": "output_text"
        }
      ],
      "id": "msg_b188058f-8225-4642-90e6-da7112f96b69",
      "role": "assistant",
      "status": "completed",
      "type": "message"
    }
  ],
  "parallel_tool_calls": true,
  "presence_penalty": 0,
  "previous_response_id": null,
  "prompt_cache_key": null,
  "reasoning": null,
  "safety_identifier": null,
  "service_tier": "default",
  "status": "completed",
  "store": true,
  "temperature": 1,
  "text": {
    "format": {
      "type": "text"
    }
  },
  "tool_choice": "auto",
  "tools": [
    {
      "type": "finance_search"
    }
  ],
  "top_logprobs": 0,
  "top_p": 1,
  "truncation": "disabled",
  "usage": {
    "cost": {
      "currency": "USD",
      "input_cost": 0.00189,
      "output_cost": 0.00016,
      "tool_calls_cost": 0.005,
      "total_cost": 0.00705
    },
    "input_tokens": 7570,
    "input_tokens_details": {
      "cached_tokens": 0
    },
    "output_tokens": 63,
    "output_tokens_details": {
      "reasoning_tokens": 0
    },
    "tool_calls_details": {
      "finance_search": {
        "invocation": 1
      }
    },
    "total_tokens": 7633
  },
  "user": null
}

​
Example prompts

  • Full company brief: “Give me a complete NVIDIA snapshot: valuation, segment revenue for the latest quarter, and management’s latest commentary on margins guidance.”
  • Compare companies in one request: “Compare Apple, Microsoft, and Alphabet on revenue growth, operating margin, and forward P/E for the latest fiscal year.”
  • Earnings + reaction context: “Summarize Tesla’s last earnings call, include actual vs consensus, and describe how the stock and analyst targets moved after publication.”

​
Prompt guidance

finance_search works best when the prompt states the outcome, not the data shape.
  • Start with the business question first, then include the company or ticker.
  • Add time windows when relevant (latest quarter, fiscal year to date, last 30 days).
  • Let the tool decide which specific report fields to retrieve.
Start with the configuration that matches the shape of the finance question. The YAML blocks use eval-config style; in SDK calls, model_args.tools maps to top-level tools, model_args.max_steps maps to top-level max_steps, and token and reasoning settings map to their matching request fields.
ConfigurationBest forLatencyQualityCost
Live market data and quotesReal-time prices, quotes, and latest figuresFastGoodLow
Single-company historical lookupsBasic historical financials for one company or tickerBalancedHighMedium
Multi-step financial researchCross-company comparisons and complex financial analysisThoroughHighestHigh

​
Live market data and quotes

Use this for time-sensitive answers that depend on real-time prices, quotes, or the latest market figures. It is the cheapest and fastest option while maintaining strong quality for live data lookups. 
model: perplexity/sonar
max_tokens: 1024
model_args:
  tools:
    - type: finance_search
  max_steps: 1

{
  "id": "resp_541684d6-cc46-4115-9137-bb387088bc32",
  "object": "response",
  "model": "perplexity/sonar",
  "status": "completed",
  "created_at": 1777645562,
  "completed_at": 1777645562,
  "output": [
    {
      "type": "finance_results",
      "categories": ["quote"],
      "tickers": ["AAPL"],
      "results": [
        {
          "category": "quote",
          "tickers": ["AAPL"],
          "content": "## AAPL Quote\n| symbol | name | timestamp | market_status | price | currency | change | changesPercentage | marketCap | pe | eps | volume | dayLow | dayHigh | yearLow | yearHigh | previousClose | open |\n| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |\n| AAPL | Apple Inc. | 2026-05-01 14:26:00 UTC | open | 285.74 | USD | 14.39 | 5.30 | 4,194,988,943,600 | 34.51 | 8.28 | 29,155,124 | 278.37 | 287.21 | 193.25 | 288.62 | 271.35 | 278.86 |",
          "sources": [
            "https://www.perplexity.ai/finance/AAPL/historical-data",
            "https://www.perplexity.ai/finance/AAPL"
          ]
        }
      ]
    },
    {
      "type": "message",
      "id": "msg_d8c03075-799d-4d4d-8feb-cc95824db262",
      "role": "assistant",
      "status": "completed",
      "content": [
        {
          "type": "output_text",
          "text": "Apple (AAPL) is currently trading at **$285.74** per share, up about 5.30% on the day. Its latest market capitalization is approximately **$4.19 trillion**.",
          "annotations": [],
          "logprobs": []
        }
      ]
    }
  ],
  "tools": [{"type": "finance_search"}],
  "max_output_tokens": 8192,
  "tool_choice": "auto",
  "parallel_tool_calls": true,
  "usage": {
    "input_tokens": 7575,
    "output_tokens": 75,
    "total_tokens": 7650,
    "cost": {
      "currency": "USD",
      "input_cost": 0.00189,
      "output_cost": 0.00019,
      "tool_calls_cost": 0.005,
      "total_cost": 0.00708
    },
    "tool_calls_details": {
      "finance_search": {
        "invocation": 1
      }
    }
  }
}

​
Single-company historical lookups

Use this for a single company’s historical figures or basic questions that benefit from both structured finance data and web context. GPT-5.5 is strong at simple web search and token-efficient for historical lookups. 
model: openai/gpt-5.5
model_args:
  max_steps: 5
  max_tokens: 2048
  reasoning_effort: low
  tools:
    - type: web_search
    - type: finance_search
    - type: fetch_url

{
  "id": "resp_1be7ab7e-0dda-4949-9578-1462f9557a6b",
  "object": "response",
  "model": "openai/gpt-5.5",
  "status": "completed",
  "created_at": 1777645563,
  "completed_at": 1777645563,
  "output": [
    {
      "type": "finance_results",
      "categories": ["financials"],
      "tickers": ["MSFT"],
      "results": [
        {
          "category": "financials",
          "tickers": ["MSFT"],
          "content": "## MSFT FY 2024\n| date | period | income_statement_total_revenues |\n| --- | --- | --- |\n| 2024-06-30 | 2024 FY | 245,122,000,000 |",
          "sources": [
            "https://www.perplexity.ai/finance/MSFT/financials?period=annual&category=INCOME_STATEMENT&fromYear=2024&toYear=2024"
          ]
        }
      ]
    },
    {
      "type": "finance_results",
      "categories": ["financials"],
      "tickers": ["MSFT"],
      "results": [
        {
          "category": "financials",
          "tickers": ["MSFT"],
          "content": "## MSFT FY 2025\n| date | period | income_statement_total_revenues |\n| --- | --- | --- |\n| 2025-06-30 | 2025 FY | 281,724,000,000 |",
          "sources": [
            "https://www.perplexity.ai/finance/MSFT/financials?period=annual&category=INCOME_STATEMENT&fromYear=2025&toYear=2025"
          ]
        }
      ]
    },
    {
      "type": "message",
      "id": "msg_99ccfbfd-bce8-4b9b-b412-b01ef45c7842",
      "role": "assistant",
      "status": "completed",
      "content": [
        {
          "type": "output_text",
          "text": "Microsoft's revenue in its last completed fiscal year, **FY2025 ended June 30, 2025**, was **$281.724 billion**.\n\nCompared with the prior year, **FY2024 revenue was $245.122 billion**, so Microsoft revenue increased by:\n\n- **$36.602 billion**\n- **About 14.9% year over year**",
          "annotations": [],
          "logprobs": []
        }
      ]
    }
  ],
  "tools": [
    {"type": "web_search"},
    {"type": "fetch_url"},
    {"type": "finance_search"}
  ],
  "max_output_tokens": 8192,
  "tool_choice": "auto",
  "parallel_tool_calls": true,
  "usage": {
    "input_tokens": 12522,
    "input_tokens_details": {
      "cached_tokens": 3840,
      "cache_read_input_tokens": 3840
    },
    "output_tokens": 500,
    "total_tokens": 13022,
    "cost": {
      "currency": "USD",
      "input_cost": 0.04341,
      "cache_read_cost": 0.00192,
      "output_cost": 0.015,
      "tool_calls_cost": 0.01,
      "total_cost": 0.07033
    },
    "tool_calls_details": {
      "finance_search": {
        "invocation": 2
      }
    }
  }
}

​
Multi-step financial research

Use this for cross-company comparisons, longer historical investigations, and analysis that needs several tool calls across financial statements, filings, transcripts, and web sources. Opus performs best on complex multi-step reasoning when paired with the full tool suite. 
model: anthropic/claude-opus-4-7
max_tokens: 4096
model_args:
  tools:
    - type: web_search
    - type: finance_search
    - type: fetch_url
  max_steps: 10

{
  "id": "resp_466bc636-cbad-43ce-9f66-c8b296712f05",
  "object": "response",
  "model": "anthropic/claude-opus-4-7",
  "status": "completed",
  "created_at": 1777645564,
  "completed_at": 1777645564,
  "output": [
    {
      "type": "finance_results",
      "categories": ["financials"],
      "tickers": ["AAPL", "MSFT", "GOOGL"],
      "results": [
        {
          "category": "financials",
          "tickers": ["AAPL", "MSFT", "GOOGL"],
          "content": "## AAPL FY 2025\n| date | period | total_revenues | gross_profit | operating_profit | net_income | gross_margin | operating_margin | net_margin |\n| --- | --- | --- | --- | --- | --- | --- | --- | --- |\n| 2025-09-27 | 2025 FY | 416,161,000,000 | 195,201,000,000 | 133,050,000,000 | 112,010,000,000 | 0.47 | 0.32 | 0.27 |\n\n## MSFT FY 2025\n| 2025-06-30 | 2025 FY | 281,724,000,000 | 193,893,000,000 | 128,528,000,000 | 101,832,000,000 | 0.69 | 0.46 | 0.36 |\n\n## GOOGL FY 2025\n| 2025-12-31 | 2025 FY | 402,836,000,000 | 240,301,000,000 | 129,039,000,000 | 132,170,000,000 | 0.60 | 0.32 | 0.33 |"
        }
      ]
    },
    {
      "type": "finance_results",
      "categories": ["financials"],
      "tickers": ["AAPL", "MSFT", "GOOGL"],
      "results": [
        {
          "category": "financials",
          "content": "## AAPL FY 2024\n| 2024-09-28 | 2024 FY | 391,035,000,000 | ... | 0.46 | 0.32 | 0.24 |\n\n## MSFT FY 2024\n| 2024-06-30 | 2024 FY | 245,122,000,000 | ... | 0.70 | 0.45 | 0.36 |\n\n## GOOGL FY 2024\n| 2024-12-31 | 2024 FY | 350,018,000,000 | ... | 0.58 | 0.32 | 0.29 |"
        }
      ]
    },
    {
      "type": "finance_results",
      "categories": ["financials"],
      "tickers": ["AAPL", "MSFT", "GOOGL"],
      "results": [
        {
          "category": "financials",
          "content": "## AAPL FY 2023 — total revenue 383,285,000,000 (GM 0.44 / OpM 0.30 / NM 0.25)\n## MSFT FY 2023 — total revenue 211,915,000,000 (GM 0.69 / OpM 0.42 / NM 0.34)\n## GOOGL FY 2023 — total revenue 307,394,000,000 (GM 0.57 / OpM 0.27 / NM 0.24)"
        }
      ]
    },
    {
      "type": "finance_results",
      "categories": ["transcript"],
      "tickers": ["AAPL", "MSFT", "GOOGL"],
      "results": [
        {
          "category": "transcript",
          "tickers": ["AAPL"],
          "content": "AAPL Q2 2026: Revenue $111.184B (est. $109.46B), EPS $2.01 (est. $1.92). 17% revenue growth in March quarter; June guide +14-17%. GM guide 47.5-48.5%. Management flagged rising memory costs as an increasing headwind. Accelerating AI investment via Apple Intelligence; install base 2.5B devices.",
          "sources": ["https://www.perplexity.ai/finance/AAPL/earnings"]
        },
        {
          "category": "transcript",
          "tickers": ["MSFT"],
          "content": "MSFT Q3 2026: Revenue $82.886B (est. $81.44B), EPS $4.27 (est. $4.07). Revenue +18% YoY; AI ARR reached $37B (+123% YoY). CapEx >$40B next quarter, ~$190B for CY2026. Capacity-constrained through 2026. Expects double-digit revenue and operating-income growth in FY27.",
          "sources": ["https://www.perplexity.ai/finance/MSFT/earnings"]
        },
        {
          "category": "transcript",
          "tickers": ["GOOGL"],
          "content": "GOOGL Q1 2026: Revenue $109.896B (est. $106.98B), EPS $5.11 (est. $2.64). 22% revenue growth; Search +19%, Cloud +63%. Operating margin 36.1%. 2026 CapEx raised to $180-190B; 2027 CapEx to significantly increase. Cloud margin headwind from Wiz acquisition.",
          "sources": ["https://www.perplexity.ai/finance/GOOGL/earnings"]
        }
      ]
    },
    {
      "type": "message",
      "id": "msg_90e83fe4-f020-47f0-990e-f82aa0b655da",
      "role": "assistant",
      "status": "completed",
      "content": [
        {
          "type": "output_text",
          "text": "# Apple vs. Microsoft vs. Alphabet — 3-Year Comparison\n\n## 1. Revenue Growth\n| Company | FY2023 | FY2024 | FY2025 | 2-yr CAGR | YoY FY25 |\n|---|---|---|---|---|---|\n| Apple (AAPL)   | $383.3B | $391.0B | $416.2B | +4.2%  | +6.4%  |\n| Microsoft (MSFT)| $211.9B | $245.1B | $281.7B | +15.3% | +14.9% |\n| Alphabet (GOOGL)| $307.4B | $350.0B | $402.8B | +14.5% | +15.1% |\n\n## 2. Margin Trends\n- Apple: GM 44% → 47%, OpM steady ~32%, NM 25% → 27%.\n- Microsoft: GM ~69% (slightly compressed by AI capex), OpM 42% → 46%, NM 34% → 36%.\n- Alphabet: GM 57% → 60%, OpM 27% → 32% (largest expansion), NM 24% → 33%.\n\n## 3. Management Commentary (latest calls)\n- Apple (Q2 FY26): Revenue +17%, June guide +14-17%; flagging memory-cost headwind.\n- Microsoft (Q3 FY26): Revenue +18%; AI ARR $37B (+123%); CY26 capex ~$190B.\n- Alphabet (Q1 2026): Revenue +22%; Cloud +63%; CY26 capex raised to $180-190B; 2027 capex to significantly increase.\n\n## Bottom Line\n- Revenue growth: Microsoft (closely followed by Alphabet)\n- Margin level: Microsoft\n- Margin expansion: Alphabet\n- Capital intensity: Apple is lightest; MSFT and GOOGL each spending $180-190B on 2026 capex.\n\nKey tension: AI investment is fueling top-line acceleration (especially MSFT and GOOGL) but creating depreciation and component-cost headwinds that are starting to weigh on gross margins.",
          "annotations": [],
          "logprobs": []
        }
      ]
    }
  ],
  "tools": [
    {"type": "web_search"},
    {"type": "fetch_url"},
    {"type": "finance_search"}
  ],
  "max_output_tokens": 8192,
  "tool_choice": "auto",
  "parallel_tool_calls": true,
  "usage": {
    "input_tokens": 61887,
    "input_tokens_details": {
      "cached_tokens": 36778,
      "cache_creation_input_tokens": 25100,
      "cache_read_input_tokens": 36778
    },
    "output_tokens": 3456,
    "total_tokens": 65343,
    "cost": {
      "currency": "USD",
      "input_cost": 0.00005,
      "cache_creation_cost": 0.15688,
      "cache_read_cost": 0.01839,
      "output_cost": 0.0864,
      "tool_calls_cost": 0.02,
      "total_cost": 0.28172
    },
    "tool_calls_details": {
      "finance_search": {
        "invocation": 4
      }
    }
  }
}

​
Pricing

finance_search is billed at $5 per 1,000 invocations. Model token usage is billed separately according to Agent API token pricing.
Pricing follows the same pattern as other tool calls: pay for invocations plus model tokens. See Pricing.

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Next Steps

Tools Overview

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