# supermemory vs TinyFish

supermemory records 156,579 monthly visits with -7.7% month-over-month growth and Contact for Pricing pricing. TinyFish records 1,124,952 monthly visits with +199.7% growth and Freemium, Contact for Pricing pricing.

| Metric | [supermemory](https://openaitools.app/tool/supermemory-1) | [TinyFish](https://openaitools.app/tool/tinyfish) |
| :--- | :--- | :--- |
| Website URL | https://supermemory.ai | https://www.tinyfish.ai |
| Categories | AI API, Large Language Models (LLMs), AI Developer Tools, AI Agent | AI API, AI Agent, AI Browsers, AI Web Scraping |
| Pricing Model | Contact for Pricing | Freemium, Contact for Pricing |
| Monthly Visits | 156,579 | 1,124,952 |
| MoM Growth Rate | -7.7% | +199.7% |
| Primary Market | United States | United States |
| Direct Visits | 71,163 | 401,320 |
| Review Score | 4.5 | 4.4 |
| Saved Count | 0 | 0 |
| Supported Platforms | Website | Website |

## supermemory

Most LLM applications treat memory as an afterthought: chat history is stuffed into the prompt until the window fills up, and everything is lost on the next session or the next model switch. supermemory attacks that problem as infrastructure. Its learner-1 model reads incoming material — conversations, files, URLs, raw data — and performs update, merge, infer and forget operations against a vector-graph database, so learnings stay dense, interconnected and time-aware rather than piling up as an ever-growing transcript.

At request time the relevant memories are injected as tokens directly into the agent's context, which keeps the approach model-agnostic and harness-agnostic. Because learning and memory live outside the model providers, the same accumulated understanding travels with an application whether it runs on Claude, GPT-family models, Gemini or open-weight models, and whether it is driven by an SDK, a plugin or MCP.

The company positions this as the hard part of agent infrastructure and backs it with published numbers: sub-second recall on production traffic, roughly a trillion tokens processed per month, benchmarks on LongMemEval, LoCoMo and ConvoMem, and cost comparisons against markdown-file memory at large corpora. Enterprise features include SOC 2 Type II certification, a HIPAA BAA on higher tiers, GDPR compliance and deployment options ranging from cloud to VPC, on-premises and air-gapped environments.

**Pricing & Plans:** Pricing is split between self-serve tiers and enterprise contracts, which is why the site lists a contact-for-pricing model. Free, Pro and Max tiers cover standard PDF extraction and personal use, while Scale and Enterprise add advanced document extraction with OCR and figure/diagram descriptions, higher limits, security guarantees such as SOC 2 Type II and HIPAA BAA, and deployment choices including your VPC, your data center or air-gapped setups. Exact figures should be confirmed on the pricing page for current rates.

- **learner-1 memory model:** A dedicated model extracts, merges, infers and forgets across stored context so the memory graph keeps improving instead of simply accumulating.
- **Vector-graph memory store:** Learnings link to the entities, sources and moments around them, storing not just content but a time-aware map of how facts relate.
- **Model, harness and MCP agnostic:** Memory lives outside model providers and is used through APIs, SDKs, plugins and MCP, so context carries across models and tools.
- **Real-time context injection:** Relevant memories are injected as tokens into the prompt at request time, giving agents relevant context without unbounded transcripts.
- **Enterprise deployment and compliance:** SOC 2 Type II, HIPAA BAA on higher tiers, GDPR compliance, plus deployment in the cloud, your VPC, your data center or air-gapped.

**Strengths:** Memory is decoupled from model providers, so accumulated context survives model swaps; Rich engineering evidence, including published benchmarks, latency figures and cost comparisons; Multiple integration surfaces — REST API, SDKs, plugins and MCP; Strong enterprise posture with SOC 2 Type II, HIPAA BAA, GDPR and air-gapped deployment options

**Limitations:** Self-serve pricing on the public site is thin, and exact tier costs may require a sales conversation; It is infrastructure rather than an end-user app, so there is real integration work before you see value; Benchmark results and adoption figures are vendor-reported and worth validating against your own workload

[Profile (Markdown)](https://openaitools.app/tool/supermemory-1.md)

## TinyFish

TinyFish describes itself as the web stack for AI agents: a serverless platform that lets agents search, extract, browse and act on the live web. Rather than a single point tool, it groups several products under one API key and one wallet — TinySearch for fresh, browser-rendered web search returned as structured JSON, TinyFetch for turning any URL into clean Markdown, JSON or HTML, TinyBrowser for real cloud browser sessions driven with Playwright, Puppeteer or CDP, TinyAgent for plain-English multi-step automation, and TinyMonitor for alerts when a page or topic changes.

The platform is aimed at production workloads rather than demos. It emphasises reliability and structure, real browser rendering instead of thin cached results, persistent session state, and the ability to handle authenticated flows. Supporting pieces include TinyVault for connecting 1Password or Bitwarden so credentials stay hidden from the model, TinyProfiles for saving signed-in sessions, and step-by-step run recordings so you can audit exactly what an agent did on a site.

TinyFish is designed to slot into existing developer stacks. It is promoted for use alongside Claude, ChatGPT, Cursor and other agent runtimes, offers an MCP connection, Python SDK and CLI, and is positioned for workloads such as price monitoring, record enrichment, deep research and supplier-portal automation. Entry-level search and fetch calls are free, while agent steps, browser minutes and monitoring checks are metered on a pay-as-you-go wallet basis, with an enterprise track for larger deployments.

**Pricing & Plans:** Freemium and usage-based. Search and basic fetch are free with no search fee, while TinyAgent is billed per step, TinyBrowser per minute and TinyMonitor per check from a prepaid wallet; new users can claim a small free credit. Enterprise plans are custom — confirm current rates on the pricing page.

- **TinySearch:** Real browser-rendered search that returns structured JSON with fresh, uncached results from the live web, with no search fee.
- **TinyFetch:** Convert any URL into token-efficient Markdown, JSON or HTML, stripping navigation bars, cookie banners and ads before they reach your model.
- **TinyBrowser:** Full cloud browser sessions with persistent state that you drive with Playwright, Puppeteer or the Chrome DevTools Protocol.
- **TinyAgent and TinyMonitor:** Give an agent a goal in plain English and it navigates, fills forms and returns structured results; monitoring fires alerts when a tracked page or topic changes.
- **One API key, one wallet:** Search, fetch, browser and agent products share single authentication and billing, plus an MCP connection, Python SDK and CLI.

**Strengths:** Consolidates search, fetch, browsing, agent automation and monitoring behind one API key and wallet; Browser-rendered, uncached results rather than thin cached snippets; Free search and fetch tiers lower the cost per task compared to several paid search APIs; Strong developer ergonomics: MCP, Python SDK, CLI and integrations with popular agent runtimes

**Limitations:** Agent steps, browser minutes and monitoring checks are metered, so heavy automation volumes add up; More complex auth flows still carry the usual fragility of driving third-party sites; It is infrastructure for builders — not aimed at non-technical end users

[Profile (Markdown)](https://openaitools.app/tool/tinyfish.md)

## Frequently Asked Questions

### How do supermemory and TinyFish compare in monthly traffic?

supermemory has 156,579 monthly visits, while TinyFish has 1,124,952. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

supermemory has a month-over-month growth rate of -7.7%; TinyFish has +199.7%.

### How does pricing compare?

supermemory: Contact for Pricing. Pricing is split between self-serve tiers and enterprise contracts, which is why the site lists a contact-for-pricing model. Free, Pro and Max tiers cover standard PDF extraction and personal use, while Scale and Enterprise add advanced document extraction with OCR and figure/diagram descriptions, higher limits, security guarantees such as SOC 2 Type II and HIPAA BAA, and deployment choices including your VPC, your data center or air-gapped setups. Exact figures should be confirmed on the pricing page for current rates. TinyFish: Freemium, Contact for Pricing. Freemium and usage-based. Search and basic fetch are free with no search fee, while TinyAgent is billed per step, TinyBrowser per minute and TinyMonitor per check from a prepaid wallet; new users can claim a small free credit. Enterprise plans are custom — confirm current rates on the pricing page.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Apify](https://openaitools.app/tool/apify) | 4,147,762 | +3.9% | Freemium, Contact for Pricing | Features a massive marketplace of ready-to-run scrapers, though it operates more as an actor platform than a raw API. | [.md](https://openaitools.app/tool/apify.md) |
| 2 | [Composio](https://openaitools.app/tool/composio) | 2,782,603 | +22.8% | Freemium, Contact for Pricing | Focuses on tool integrations and authentication for agents, complementing memory engines rather than storing cross-session context. | [.md](https://openaitools.app/tool/composio.md) |
| 3 | [Firecrawl](https://openaitools.app/tool/firecrawl-dev) | 1,828,239 | -1.9% | Freemium, Contact for Pricing | Provides cleaner LLM-ready markdown conversion and crawling, but lacks TinyFish's interactive cloud browser automation capabilities. | [.md](https://openaitools.app/tool/firecrawl-dev.md) |
| 4 | [Exa](https://openaitools.app/tool/exa-ai) | 1,062,574 | +16.8% | Freemium, Contact for Pricing | Offers superior neural web search designed for AI agents, but provides less comprehensive raw browser automation tools. | [.md](https://openaitools.app/tool/exa-ai.md) |
| 5 | [Bright Data](https://openaitools.app/tool/bright-data) | 802,752 | -5.9% | Free Trial, Paid | Delivers enterprise-grade proxy networks and scraping infrastructure, but involves a steeper learning curve than TinyFish. | [.md](https://openaitools.app/tool/bright-data.md) |
| 6 | [LiteLLM](https://openaitools.app/tool/litellm) | 576,967 | +7.9% | Freemium, Contact for Pricing | One open-source AI gateway for 100+ LLM providers | [.md](https://openaitools.app/tool/litellm.md) |
| 7 | [Merge](https://openaitools.app/tool/merge-dev) | 313,201 | +1.7% | Freemium, Contact for Pricing | The universal context engine connecting agents to data, tools, and models | [.md](https://openaitools.app/tool/merge-dev.md) |
| 8 | [Pinecone](https://openaitools.app/tool/pinecone) | 286,732 | -31% | Freemium, Paid, Contact for Pricing | Offers enterprise-grade scalable vector search and RAG storage, but lacks supermemory's automated agent memory graph abstractions. | [.md](https://openaitools.app/tool/pinecone.md) |
| 9 | [Jina AI](https://openaitools.app/tool/jina-ai) | 280,782 | -16.5% | Freemium, Paid | Excels at converting URLs into clean markdown and embeddings, but lacks dedicated browser actuation and live search endpoints. | [.md](https://openaitools.app/tool/jina-ai.md) |
| 10 | [Portkey](https://openaitools.app/tool/portkey-ai) | 195,650 | -9.4% | Freemium, Paid, Contact for Pricing | AI gateway, observability and guardrails for production LLM apps | [.md](https://openaitools.app/tool/portkey-ai.md) |

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Source: https://openaitools.app/compare/supermemory-1-vs-tinyfish

More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)