TinyFish vs Firecrawl: Web Extraction & AI Agents
Firecrawl and TinyFish both help developers retrieve information from websites and build AI-powered web workflows. Firecrawl provides scraping, crawling, search, extraction, interaction and agent capabilities, while TinyFish offers TinySearch, TinyFetch, TinyBrowser, TinyAgent, TinyMonitor and TinySet APIs.
Their capabilities increasingly overlap, but developers still need to evaluate how each platform handles bulk extraction, autonomous interaction, authenticated workflows, pricing, and operational requirements.
This comparison examines those differences, including when a dedicated crawling pipeline makes sense and when managed web agent execution may be more suitable.
For a broader feature overview, see our TinyFish vs Firecrawl Comparison.
Quick Reference: Which Tool Fits Your Situation?
| Requirement | What to evaluate |
|---|---|
| Crawl an entire documentation site | Firecrawl Crawl and Map |
| Retrieve content from known URLs | Firecrawl Scrape and TinyFish Fetch |
| Search for relevant web pages | Firecrawl Search and TinyFish Search |
| Interact with dynamic websites | Firecrawl Interact, Firecrawl Agent, and TinyFish Agent |
| Complete multi-step tasks | Firecrawl Agent and TinyFish Agent |
| Run existing automation scripts | The platforms' relevant managed browser offerings |
| Self-host crawling infrastructure | Firecrawl's supported self-hosted components |
| Run managed agent workflows | Compare execution results, configuration, and pricing |
What Each Product Actually Does
Firecrawl is a web scraping and crawling API. It converts raw web pages into clean markdown or structured JSON — formats designed for LLM consumption, RAG pipelines, and AI agent workflows. The product surface is broad:
- /scrape — extract a single page
- /crawl — recursively discover and scrape an entire domain
- /map — return all URLs on a site in seconds
- /extract — LLM-powered structured data extraction with Pydantic schemas
- /agent — autonomous browsing from a natural language prompt (powered by FIRE-1)
- /interact — scrape a page, then take actions on it
Firecrawl is open source (AGPL-3.0 core, Fire-Engine proprietary), self-hostable, and integrates natively with LangChain, LlamaIndex, n8n, Zapier, and MCP. Over 500K developers and 80K+ companies use it. Customers include Shopify, Zapier, Canva, and Apple.
TinyFish is a web agent platform. You describe a task in plain English, and TinyFish runs a full browser session — navigating, interacting, authenticating, and extracting — then returns structured JSON.
One endpoint. One API key. Browser, LLM inference, and infrastructure-level handling all included — no separate line items.
Enterprise customers include global platforms in travel, food delivery, and fitness.
Firecrawl has expanded from its original scraping and crawling capabilities into broader agent workflows. TinyFish offers a separate set of web data and execution APIs built around managed browser infrastructure. Developers should compare the products at the endpoint and workflow level rather than assuming that one platform supports extraction while the other supports interaction.
Where Firecrawl Wins
Give credit where it's due.
Full-site crawling. Firecrawl's /crawl endpoint recursively discovers and extracts content across an entire domain. The /map endpoint returns every URL on a site in seconds. If you're building a RAG pipeline that needs to ingest an entire documentation site or knowledge base, this is purpose-built for the job. TinyFish can navigate multiple pages via its agent, but it doesn't have a dedicated crawl endpoint — it's designed for targeted workflows, not bulk content ingestion.
Open source and self-hostable. The core is AGPL-3.0. If your organization requires code inspection, self-deployment, or data residency, Firecrawl gives you that option. TinyFish is a managed service — you can't run it on your own infrastructure (outside of Enterprise on-premise options).
Ecosystem breadth. Native integrations with LangChain, LlamaIndex, Zapier, Make, n8n, and a growing list of AI frameworks. 103K GitHub stars means a large community building extensions, writing tutorials, and reporting bugs. For developer adoption, this ecosystem is hard to beat.
Pydantic schema extraction. The /extract endpoint lets you define exact data schemas using Pydantic, and Firecrawl's LLM fills them in. For teams that need predictable, typed output structures from static pages, this is cleaner than free-form goal descriptions.
Where the Gap Opens
Firecrawl's strengths are in content extraction — getting data off pages that are already accessible. Both platforms now support more than simple page extraction. The practical differences appear when developers compare specific workflow requirements, including session management, authentication, multi-page navigation, structured results, and recovery from unexpected website states.
Authentication and session management: Workflows involving logged-in websites require secure credentials, valid sessions, and appropriate authorization. Firecrawl's browser and agent capabilities should be evaluated for the relevant authentication flow, while TinyFish provides Browser Profiles and Vault for supported authenticated workflows. The comparison should focus on how credentials are stored, sessions are reused, and authentication failures are handled
Multi-step interaction: Firecrawl provides interaction and autonomous agent functionality, while TinyFish Agent also supports goal-directed navigation and multi-step website tasks. Developers should compare how each product handles conditional navigation, unexpected page states, structured output requirements, and unsuccessful task execution.
Sites with strict automation requirements:Websites with strict access controls can introduce additional challenges for browser automation and data extraction. Both platforms provide infrastructure intended to support web data workflows, but reliability depends on the target website, authorization, session state, and product configuration. Teams should test representative sources and compare successful results rather than relying on general claims about protected-site coverage.
For more information, see our guide to anti-bot protection for web agents
Geographic routing: TinyFish supports geographic proxy routing (US, GB, CA, DE, FR, JP, AU) with a single parameter. Sites that serve different content based on location — pricing pages, regional catalogs, geo-restricted content — are handled natively.
Pricing: Credits vs Steps
The pricing models look similar on the surface — both are usage-based — but the mechanics are different.
Firecrawl: Credits with multipliers
Firecrawl uses a credit-based model for scraping, crawling, search, and interaction features. Basic scraping costs one credit per page, while other endpoints and additional extraction features can consume more credits.
As of October 2026, Firecrawl's published free tier includes 1,000 credits per month. Search costs two credits per 10 results, Interact costs two credits per browser minute, and Agent uses dynamic pricing with a limited daily free allowance.
Developers should calculate costs using the specific endpoints required for their workflow rather than comparing monthly credit allocations alone.
TinyFish: Agent Steps and Browser Minutes
TinyFish uses Wallet-based pricing with separate rates for its products. Search and Fetch are free within their standard limits. Agent costs $0.016 per step, and Browser costs $0.002 per minute.
Agent execution includes the supporting model inference and managed execution infrastructure, while Browser sessions are metered by duration. Developers should compare the cost of completing an equivalent task rather than treating credits, steps, and browser minutes as directly interchangeable.
The real cost comparison
Consider two workloads: extracting content from 100 public product pages and collecting pricing information from authenticated supplier portals.
For public pages with predictable structures, compare the cost of Firecrawl Scrape with TinyFish Fetch before considering more expensive execution methods. For authenticated or interactive workflows, compare Firecrawl's relevant agent or interaction offering against TinyFish Agent.
The useful measure is cost per successfully completed task, including retries, data validation, infrastructure charges, and ongoing engineering maintenance.
Firecrawl Agent vs TinyFish Agent: Workflow Comparison
Firecrawl Agent and TinyFish Agent both support natural-language instructions for collecting information and interacting with websites. To compare them fairly, developers should test the same workflow with equivalent instructions, expected output fields, and success criteria.
A useful test is to retrieve information from a multi-page website, apply a filter, navigate to the relevant result, and return structured data. The evaluation should record completion status, output accuracy, execution time, billed usage, and any manual intervention required.
| Evaluation criterion | Firecrawl Agent | TinyFish Agent |
|---|---|---|
| Instructions | Natural-language task | Natural-language goal |
| Navigation | Supported | Supported |
| Structured output | Supported | Supported |
| Authentication | Evaluate selected workflow | Profiles/Vault where supported |
| Error handling | Compare execution results | Compare execution results |
| Pricing | Dynamic Agent pricing | $0.016/step |
| Task success | Requires testing | Requires testing |
When to Use Both
Firecrawl can serve bulk crawling and content-ingestion workflows, while TinyFish can provide additional options for web discovery, managed browser execution, and goal-directed tasks.
For example, a pipeline might use Firecrawl to discover and retrieve public documentation pages, then use TinyFish Agent for a separate workflow requiring interaction with an authorized account.
Combining tools is useful when each component serves a distinct requirement. It is not necessary when one platform already supports the complete workflow at an acceptable cost.
Decision Framework
Choose Firecrawl if you:
- Need to crawl and extract content from large numbers of public pages.
- Want structured website content for knowledge bases, research, or RAG pipelines.
- Need Firecrawl's dedicated scraping and crawling endpoints.
- Want to evaluate its interaction and agent capabilities within your existing data pipeline.
Choose TinyFish if you:
- Want free Search and Fetch APIs for web discovery and retrieving content from known URLs.
- Need managed browser sessions for compatible automation workflows.
- Want to execute multi-step website tasks using natural-language instructions.
- Prefer step-based Agent billing with managed model inference and execution infrastructure.
Use both if:
Your workflow benefits from Firecrawl's crawling capabilities alongside TinyFish’s Search, Fetch, Browser, or Agent APIs. Evaluate the combination based on actual requirements rather than assuming both services are necessary.
Try It on a Real Workflow
Both platforms offer ways to test their capabilities before committing to a larger deployment. Choose a representative website and evaluate the same task using the relevant Firecrawl and TinyFish products. Compare the accuracy of the result, execution time, billed usage, and amount of configuration required.
TinyFish provides $8 in Wallet funds for new accounts, allowing developers to test Agent and Browser workflows without an initial deposit.
Related Reading
AI disclosure
Content on this website may be created or refined with the assistance of AI tools and is subject to human editorial review.
