# Aquin vs Scalebrowser

Aquin records 0 monthly visits with 0% month-over-month growth and Contact for Pricing pricing. Scalebrowser records 161,955 monthly visits with +212.7% growth and Free Trial, Paid pricing.

| Metric | [Aquin](https://openaitools.app/tool/aquin) | [Scalebrowser](https://openaitools.app/tool/scalebrowser) |
| :--- | :--- | :--- |
| Website URL | https://www.aquin.app | https://scalebrowser.net |
| Categories | AI Browsers, AI Search Engine, AI Assistant, AI Speech-to-Text | AI Browsers, AI Agent, AI Developer Tools, AI API |
| Pricing Model | Contact for Pricing | Free Trial, Paid |
| Monthly Visits | 0 | 161,955 |
| MoM Growth Rate | 0% | +212.7% |
| Primary Market | Global | Global |
| Direct Visits | 0 | 65,234 |
| Review Score | 4.1 | 4.7 |
| Saved Count | 0 | 0 |
| Supported Platforms | Website | Website |

## Aquin

Aquin is best understood as a research lab rather than a single consumer app. The homepage describes the team as reverse engineering intelligence through interpretability, and frames its goal as applied prediction that compounds over time - systems that understand what a model has learned and that teams can point at their own data. The flagship applied product is Aleph, a universal predictor spanning tables, media, annotation and decisions.\n\nWhat separates Aleph from a general-purpose assistant is its output contract. It produces schema-bound results for programs: probabilities, labels, bounding boxes and scores, each carrying confidence so that uncertain items can be escalated rather than silently guessed. The lab positions this as 'one base, any modality, any task', fine-tuned into a specific workload and improving as more labelled work arrives.\n\nAround that core, Aquin publishes applied research on interpretability. Published work includes an interpreter for attention-as-routing-graph circuits from a single forward pass, tiled SVD methods for locating usable weight mechanisms, agentic weight-editing experiments on small models, and simulations of LLM behaviour in varied environments. Separate projects like the axi self-learning agent and the aq developer environment target people building and refining foundation models.

**Pricing & Plans:** Aquin does not publish a public price list. The site mixes freely readable research with applied engagements, so commercial terms are discussed directly with the team.

- **Universal predictor (Aleph):** A single base that handles tables, media, annotation and decision tasks, with the option to fine-tune toward your specific data.
- **Schema-bound outputs:** Outputs are typed and scored rather than free text, so downstream programs can act on results and escalate low-confidence cases.
- **Interpretability research:** Treats attention as a routing map from a single forward pass, isolating a small subgraph aimed at the answer and testing it under ablation.
- **Weight editing experiments:** Agentic weight-editing experiments that localise causal layers, apply rank-one MLP updates and validate then roll back steps when checks fail.
- **Self-learning developer agent:** An agent for controlling developer environments and running coding or research loops with recorded lessons and rejected paths.

**Strengths:** Research-grade interpretability work published openly alongside the applied product; Outputs designed for programs rather than chat, which suits automation pipelines; Explicit confidence scores make it practical to escalate uncertain predictions; One base is claimed to cover tables, media, annotation and decisions

**Limitations:** Aquin Labs is a research organisation, so most output is papers and interfaces rather than a polished consumer app; Aleph is described as a predictor for programs and teams, not a general chat assistant; No transparent public price list was found for commercial engagements; Material is heavily technical and assumes familiarity with ML evaluation work

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

## Scalebrowser

>Scalebrowser targets the part of agent work that usually breaks first: staying authenticated. Instead of scraping a signed-out page or re-logging in on every run, it hands each agent a browser machine that keeps a stable identity, complete with stored passwords, per-profile inboxes, two-factor codes and passkeys. The product installs as a desktop app so the GPU, screen and fingerprint values match the real machine, which reduces the chance that a profile contradicts itself.

On top of the browser layer, Scalebrowser adds an agent layer. Agents read a page once and then only what changed, which keeps token spend predictable on long runs. Captchas are handled through human-like input, keys on a page are surfaced to the agent as placeholders, and each tool call is logged as a step with a result and a screenshot. It works with MCP clients such as Claude and Cursor, Python and Node SDKs, a REST API and direct CDP for existing browser-use code.

Plans are measured by how much runs at once. The free tier covers a single browser and three profiles, while paid tiers grow concurrent browsers, machines, profiles and workflows. Workflows can be started by hand or by an agent, and higher tiers add schedules, webhooks, sync and phone approvals.

**Pricing & Plans:** Free plan with 1 concurrent browser, 1 machine and 3 profiles, no card required. Paid plans: Start at $19/month (1 browser, 25 profiles), Solo at $49/month (5 browsers, 100 profiles), Studio at $99/month (20 browsers, 3 machines, 500 profiles), and custom Enterprise pricing. Most paid plans include a 7-day free trial.

- **Persistent profile identity:** Each profile is generated from a seed so its identity, cookies and logins persist across restarts, and sites see the same returning visitor rather than a new device.
- **Isolated browser profiles:** One browser per profile means separate logins, cookies and devices that share nothing, making multi-account automation safe to run in parallel.
- **Built-in sign-in and 2FA handling:** Agents get through username and password forms, email confirmation codes, TOTP and SMS two-factor codes, passkeys and permission prompts without stalling.
- **Human-like input and captchas:** Press-and-hold, image grid, slider and rotation captchas are solved through human-like input rather than third-party solving keys.
- **Flexible agent integrations and trails:** Connect over MCP, Python or Node SDKs, REST or direct CDP, and review every action as a step with its result and screenshot.

**Strengths:** Strong focus on persistent, isolated identities so agents stay logged in across runs; Broad integration surface covering MCP, Python/Node SDKs, REST and direct CDP; Built-in handling of logins, email codes, TOTP, SMS, passkeys and captchas; Token-efficient page reading that only reports what changed between steps

**Limitations:** Requires installing a desktop app and running it on your own machine, so it is not a purely cloud-hosted service; Free tier excludes schedules, webhooks, sync and phone approvals; Paid tiers meter concurrent browsers, machines and profile counts, which can raise costs for large fleets; Advanced anti-detection features may raise compliance responsibility with target platforms

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

## Frequently Asked Questions

### How do Aquin and Scalebrowser compare in monthly traffic?

Aquin has 0 monthly visits, while Scalebrowser has 161,955. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Aquin has a month-over-month growth rate of 0%; Scalebrowser has +212.7%.

### How does pricing compare?

Aquin: Contact for Pricing. Aquin does not publish a public price list. The site mixes freely readable research with applied engagements, so commercial terms are discussed directly with the team. Scalebrowser: Free Trial, Paid. Free plan with 1 concurrent browser, 1 machine and 3 profiles, no card required. Paid plans: Start at $19/month (1 browser, 25 profiles), Solo at $49/month (5 browsers, 100 profiles), Studio at $99/month (20 browsers, 3 machines, 500 profiles), and custom Enterprise pricing. Most paid plans include a 7-day free trial.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [DeepSeek](https://openaitools.app/tool/deepseek) | 372,761,591 | +4.3% | Freemium | High-efficiency open-weight and hosted reasoning AI powered by DeepSeek-V4 and R1 at ultra-low token costs. | [.md](https://openaitools.app/tool/deepseek.md) |
| 2 | [Grok](https://openaitools.app/tool/grok) | 203,846,050 | -0.8% | Freemium | xAI's real-time AI assistant and coding workspace powered by Grok 4.7 with live X integration. | [.md](https://openaitools.app/tool/grok.md) |
| 3 | [Apify](https://openaitools.app/tool/apify) | 4,147,762 | +3.9% | Freemium, Contact for Pricing | A massive cloud web scraping and automation marketplace, though it lacks Scalebrowser's focus on persistent isolated profiles. | [.md](https://openaitools.app/tool/apify.md) |
| 4 | [Dia Browser](https://openaitools.app/tool/dia-browser) | 1,254,172 | +108.4% | Free | The AI browser that reads between your tabs | [.md](https://openaitools.app/tool/dia-browser.md) |
| 5 | [Labelbox](https://openaitools.app/tool/labelbox) | 762,803 | -22.8% | Contact for Pricing | The environments frontier AI trains on, and the agents that do the recurring work | [.md](https://openaitools.app/tool/labelbox.md) |
| 6 | [Eigent AI](https://openaitools.app/tool/eigent-ai) | 575,703 | +1.4% | Freemium, Free Trial, Contact for Pricing | Open-source desktop AI workforce that runs browser, file, and app tasks for you | [.md](https://openaitools.app/tool/eigent-ai.md) |
| 7 | [Vocareum](https://openaitools.app/tool/vocareum-com) | 531,556 | +5.4% | Paid | Hands-on lab infrastructure for AI, cloud, and data education | [.md](https://openaitools.app/tool/vocareum-com.md) |
| 8 | [ego (lite)](https://openaitools.app/tool/ego-lite) | 384,099 | +97.6% | Free | A free Chromium-based browser optimized for running parallel AI web automation and scraping tasks locally. | [.md](https://openaitools.app/tool/ego-lite.md) |
| 9 | [Deep Search](https://openaitools.app/tool/deep-search) | 359,001 | -52.7% | Paid | AI-enriched people profiles built from the public web, with sources you can verify | [.md](https://openaitools.app/tool/deep-search.md) |
| 10 | [Happycapy](https://openaitools.app/tool/happycapy) | 191,406 | +7.2% | Freemium | An agent-native computer that works while you sleep | [.md](https://openaitools.app/tool/happycapy.md) |

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Source: https://openaitools.app/compare/aquin-vs-scalebrowser

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