# EverMemOS vs Vana

EverMemOS records 24,237 monthly visits with +12% month-over-month growth and Free Trial, Free pricing. Vana records 5,701 monthly visits with -45.5% growth and Free pricing.

| Metric | [EverMemOS](https://openaitools.app/tool/evermemos) | [Vana](https://openaitools.app/tool/vana-com) |
| :--- | :--- | :--- |
| Website URL | https://evermind.ai | https://vana.com |
| Categories | AI Developer Tools, AI Agent, Open Source AI Models, AI Models | AI Models, Open Source AI Models, Large Language Models (LLMs), Web3 |
| Pricing Model | Free Trial, Free | Free |
| Monthly Visits | 24,237 | 5,701 |
| MoM Growth Rate | +12% | -45.5% |
| Primary Market | United States | United States |
| Direct Visits | 14,588 | 2,339 |
| Review Score | 4.4 | 4.2 |
| Saved Count | 1 | 8 |
| Supported Platforms | Website | Website |

## EverMemOS

Modern LLMs forget. Context windows cap out, RAG returns similar text without real understanding, and most memory systems are built for one user and one model. EverMemOS, the flagship product of EverMind's product family alongside the EverMe personal memory hub, is designed to close that gap by acting as a memory operating system for agents: persistent, proactive and self-evolving rather than stateless.

Two capabilities stand out. First, mRAG — a multimodal retrieval and ingestion layer that pulls in PDFs, images, Word documents, spreadsheets, presentations, emails, HTML pages and URLs through one API and supports cross-modal search. Second, self-evolving memory: agent trajectories are captured as Cases, repeated patterns are distilled into reusable Skills, and the agent applies those later instead of starting from scratch each session. A Memory Bank interface gives users visibility into user, group and agent memory and lets them inspect, manage and edit generated Skills.

EverMind frames memory as the difference between a tool and an agent, and backs the claim with reproducible open benchmarks — LoCoMo, LongMemEval and AMA are all listed on the site. The product family includes EverOS for developers building agent memory and EverMe as a personal memory hub. New users receive 2,000 credits on signup, and a Mac app is available.

**Pricing & Plans:** EverMind offers a free signup with 2,000 starter credits. No fixed public price list is shown for the cloud platform, and the company positions its memory infrastructure with free and open-source components alongside paid plans.

- **mRAG multimodal memory:** Multimodal retrieval and ingestion via a single API, covering PDFs, images, Word files, spreadsheets, decks, emails, HTML and URLs.
- **Self-evolving agent memory:** Agent trajectories are recorded as Cases, distilled into reusable Skills, and reused so performance improves over time.
- **Memory Bank transparency:** Inspect, manage and edit user, group and agent memories in a dedicated Memory Bank interface.
- **Open benchmark results:** EverMind publishes reproducible results on LoCoMo, LongMemEval and AMA alongside its memory research.
- **Team and temporal memory:** Supports multi-agent coordination and group context sharing, plus temporal tracking so outdated facts are not treated as current.

**Strengths:** Tackles a real gap: persistent memory and identity for AI agents; mRAG takes many document and media types through one API; Self-evolving Skills let agents improve instead of starting from zero; Transparent Memory Bank for inspecting and editing stored memory

**Limitations:** Memory infrastructure requires developer integration effort; The memory-OS space is crowded and fast-moving, so APIs may evolve; Self-hosting the open-source core puts operational load on your team; Benchmark leadership claims still need validation on your own workloads

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

## Vana

Vana is built on a simple premise: the data people generate should belong to them, and AI should be able to learn from it only with explicit, revocable permission. To make that practical, Vana combines a peer-to-peer protocol with a data portability layer. Users connect the services they already use through open-source connectors or a desktop agent, and their Personal Server — running locally in a browser tab or bundled into the desktop app — encrypts the collected data and syncs only ciphertext to hosted storage. Nothing leaves the device in the clear, and nothing is decrypted without a permission the user has granted.

Access is handled through first-class protocol primitives: identity, permissions, fees, schemas, files and Protocol-Governed Encryption. When a builder presents a valid grant, the user's Personal Server decrypts the covered scope and returns it directly to the builder; the grant itself is recorded on-chain and every read lands in an access log the user can review. DataDAOs and pooled confidential compute sit on top as an optional application layer, letting groups contribute data to shared jobs without exposing raw records.

For developers, Vana looks like a normal SDK workflow. You install the Vana SDK, request user-approved data, read it from the user's Personal Server, and settle protocol fees from an app escrow balance. The protocol runs on the Vana L1 with the VANA token used for staking, bridging and network security. Collection, encrypted storage, on-chain primitives, the DP RPC and grant-gated access are all live on mainnet and the Moksha testnet, with confidential compute and decentralizing the sequencer on the roadmap.

**Pricing & Plans:** Vana is free to use for the core protocol and SDK. Builders pay protocol fees from an app escrow balance when reading user-approved data, and the network supports an optional USD-billing gateway for OAuth-based apps.

- **User-owned data portability:** People collect data from services they already use through open-source connectors, and that data stays on their own device or encrypted storage they control.
- **Personal Server and on-chain grants:** A locally running access engine encrypts data and releases it only against a valid on-chain permission, with every read written to a reviewable access log.
- **Vana SDK for builders:** Install @opendatalabs/vana-sdk to request user-approved data, read it from a Personal Server, and settle protocol fees from an app escrow balance.
- **DataDAOs and confidential compute:** Groups pool data for privacy-preserving compute jobs, so contributions can be used by AI without exposing raw records.
- **Vana L1 and VANA token:** The protocol settles on its own L1 with validators, core contracts, and the VANA token used for staking and bridging.

**Strengths:** Genuine user-ownership model: local encryption, on-chain grants, and a reviewable access log instead of silent data sharing; Public, well-structured developer documentation with an SDK, CLI, and protocol spec; Open-source connectors and a permissionless direct SDK path keep the network from depending on a single operator; Live on mainnet with a clear roadmap for confidential compute and sequencer decentralization

**Limitations:** Requires understanding of wallets, encryption concepts, and grants, which is heavy for non-technical users; Parts of the hosted stack (RPC gateway, Context Gateway) are still operated by Open Data Labs; Confidential compute and Protocol-Governed Encryption are partly in progress rather than fully shipped

[Profile (Markdown)](https://openaitools.app/tool/vana-com.md)

## Frequently Asked Questions

### How do EverMemOS and Vana compare in monthly traffic?

EverMemOS has 24,237 monthly visits, while Vana has 5,701. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

EverMemOS has a month-over-month growth rate of +12%; Vana has -45.5%.

### How does pricing compare?

EverMemOS: Free Trial, Free. EverMind offers a free signup with 2,000 starter credits. No fixed public price list is shown for the cloud platform, and the company positions its memory infrastructure with free and open-source components alongside paid plans. Vana: Free. Vana is free to use for the core protocol and SDK. Builders pay protocol fees from an app escrow balance when reading user-approved data, and the network supports an optional USD-billing gateway for OAuth-based apps.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Ollama](https://openaitools.app/tool/ollama) | 9,421,973 | +4.3% | Free, Freemium, Paid | Run and build with open AI models locally or in the cloud | [.md](https://openaitools.app/tool/ollama.md) |
| 2 | [Gemma Open Models by Google](https://openaitools.app/tool/gemma-open-models-by-google) | 4,900,914 | -13.5% | Freemium, Paid | Google's family of lightweight, open-weight AI models | [.md](https://openaitools.app/tool/gemma-open-models-by-google.md) |
| 3 | [Hermes-Agent](https://openaitools.app/tool/hermes-agent-1) | 3,638,741 | -5.4% | Freemium | A free, open-source personal AI agent that learns your projects and works across every messaging app. | [.md](https://openaitools.app/tool/hermes-agent-1.md) |
| 4 | [ModelScope](https://openaitools.app/tool/modelscope-community) | 3,085,423 | +5.1% | Free | Open-source model and dataset hub with one-click online demos | [.md](https://openaitools.app/tool/modelscope-community.md) |
| 5 | [Composio](https://openaitools.app/tool/composio) | 2,782,603 | +22.8% | Freemium, Contact for Pricing | Give your AI agents secure, authenticated access to 1,700+ apps | [.md](https://openaitools.app/tool/composio.md) |
| 6 | [Exa](https://openaitools.app/tool/exa-ai) | 1,062,574 | +16.8% | Freemium, Contact for Pricing | Web search API and crawler built for AI agents | [.md](https://openaitools.app/tool/exa-ai.md) |
| 7 | [Unsloth AI](https://openaitools.app/tool/unsloth-ai) | 887,457 | -17.6% | Free | Open-source, memory-efficient fine-tuning and local model running | [.md](https://openaitools.app/tool/unsloth-ai.md) |
| 8 | [Scale](https://openaitools.app/tool/scale) | 616,915 | +12.5% | Contact for Pricing | The data, evaluations and systems behind AI that has to be right. | [.md](https://openaitools.app/tool/scale.md) |
| 9 | [Chutes](https://openaitools.app/tool/chutes) | 250,187 | -15.2% | Paid | Serverless, decentralized inference for open-source AI models | [.md](https://openaitools.app/tool/chutes.md) |
| 10 | [supermemory](https://openaitools.app/tool/supermemory-1) | 156,579 | -7.7% | Contact for Pricing | A memory and continual-learning engine that gives any AI agent persistent context | [.md](https://openaitools.app/tool/supermemory-1.md) |

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Source: https://openaitools.app/compare/evermemos-vs-vana-com

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