13 Best Embedding Models in 2025: OpenAI vs Voyage AI vs Ollama | Complete Guide + Pricing & Performance

In this guide to the top embedding models in 2025, we'll explore everything you need to know about these embedding models that are changing how AI models understand and work with text.

Here's what we're going to cover:

• The importance of embedding models explained by Dharmesh Shah from HubSpot
• What embedding models are and how they work in simple terms
• Detailed breakdown of the top 13 embedding model providers
• Each provider's best models, pricing, key features, and ideal use cases
• Technical specifications and output dimensions for all major models
• Elephas - a Mac AI assistant that simplifies the entire process without technical setup

The Importance of Embedding Models Explained by Dharmesh Shah

Dharmesh Shah, co-founder and CTO of HubSpot, recently explained on the My First Million podcast why traditional AI models fall short for business applications. He identified two critical problems: AI models don't know what they weren't trained on (your private documents), and their knowledge gets frozen at a specific training date.

Shah's solution involves using vector embeddings and semantic search. Instead of asking AI about your 100,000 company documents directly, you put them in a special vector database.

When someone asks a question, the system finds the five most relevant documents based on meaning (not just keywords) and feeds them to the AI along with the question. 

He compared this to "hiring a brilliant intern with a PhD in everything" who can instantly read any five documents you give them.

Shah uses OpenAI's embeddings API to convert each document into high-dimensional vectors (3,072 dimensions) and stores them in a vector database. When someone asks a question, the system searches these vectors to find the most semantically relevant documents, then feeds those specific documents to ChatGPT within its context window for accurate answers.

When co-host Shaan Puri asked about ready-made tools to avoid the technical complexity, Shah said he didn’t find any good ones.

What Shah Wished Existed: A Ready-Made Solution

Elephas can help with what Dharmesh Shah did, but without any technical complexities and also with complete privacy, letting you run it offline with a local LLM model. You simply upload thousands of documents, and Elephas lets you chat with your knowledge base instantly. It connects with popular tools like Notion, Obsidian, DevonThink, Roam Research, and Apple Notes, plus Elephas can work completely offline for maximum privacy.

Key Features:

• Zero Technical Setup: Upload documents and start chatting immediately
• Offline Privacy: You can run it offline making the processing happen on your Mac, no data leaves your device
• PKM Integration: Seamlessly connects with Obsidian, DevonThink, and other note-taking apps
• Multi-Format Support: Handles PDF, Word, CSV, JSON, and 10+ additional file types​
• Smart Search: Semantic search finds relevant information by meaning, not just keywords
• Different AI providers: users can also run elephas with API keys of OpenAI, Gemini, Claude etc
• Workflow automation: Automate repetitive tasks with customizable workflow agents.

Moreover, most of the best embedding models mentioned in our list are already supported by Elephas. You can choose your preferred embedding model, including local options like Ollama, within Elephas.

• Try Elepahs for free

Top 13 Best Embedding Models in 2025 at a Glance

• OpenAI: Best for companies that need reliable text understanding tools with proven enterprise support
• Voyage AI: Best for developers who want cutting-edge performance with the newest embedding technology
• Ollama: Best for developers prioritizing complete data privacy with local AI processing
• Cohere: Best for businesses working with multiple languages and need reliable multilingual processing
• Gemini: Best for developers who want high-quality embeddings without any subscription costs
• Jina AI: Best for developers who want advanced technology with open source flexibility
• Anthropic Partnership: Best for companies that prioritize safety and reliability in their AI systems
• Amazon Web Services: Best for businesses already using AWS or needing enterprise-grade security and scalability
• Mistral AI: Best for companies wanting high-quality European-developed AI technology
• Snowflake: Best for enterprises that store data in Snowflake and want native AI integration
• Hugging Face: Best for developers who want access to thousands of research models and open source freedom
• E5 (Microsoft): Best for organizations wanting enterprise-quality models without ongoing licensing costs
• BGE(Beijing Academy of AI): Best for businesses working with Chinese content or wanting top-tier open source models

Top 13 Best Embedding Models in 2025

1. OpenAI: Leading the Way in Text Understanding

Best for: Companies that need reliable text understanding tools with good support and easy setup. Works great for businesses that want proven technology without complicated setup.

OpenAI creates some of the most popular embedding models that help computers understand text better. The company launched these models in early 2024 to make it easier for businesses to build smart search systems. 

You can find detailed pricing and technical information in their official documentation. OpenAI is known for making ChatGPT and has been working on AI technology since 2015.

Their embedding models are trusted by thousands of companies around the world. These tools turn regular text into numbers that computers can work with, making search and text analysis much more accurate.

Models Provided:

• text-embedding-3-large (best overall performance and accuracy)
• text-embedding-3-small (faster processing and lower costs)
• text-embedding-ada-002 (older version still available)

Key Features:

• High Performance on English Tasks: Works very well with English text and gives accurate results for most business needs
• Adjustable Output Size: You can make the output smaller to save storage space while keeping good quality
• Easy to Use: Simple setup process with clear guides and helpful customer support
• Proven Technology: Used by many successful companies so you know it works well

Model Size & Output Dimensions:

• text-embedding-3-large: Up to 3,072 dimensions (can be made smaller)
• text-embedding-3-small: 1,536 dimensions
• Maximum text length: 8,192 tokens

Pricing:

• text-embedding-3-large: $0.13 per million tokens
• text-embedding-3-small: $0.02 per million tokens

2. Voyage AI: A New Competitor in Text Embeddings

Best for: Developers who want the newest technology with the best performance. Perfect for companies that need high-quality results while keeping costs low.

Voyage AI makes the newest and most powerful embedding models available today. The company started in 2023 and quickly became the top choice for many developers. 

You can view their complete pricing structure and model specifications in their official documentation. They focus only on making the best possible text understanding tools.

Their models beat most competitors while costing less money to use. Voyage AI has partnerships with major companies like Anthropic, who recommend them as their preferred embedding provider.

Models Provided:

• voyage-3-large (highest quality and best overall performance)
• voyage-3.5 (balanced performance and cost)
• voyage-3.5-lite (fastest and cheapest option)
• voyage-code-3 (specially made for computer code)
• voyage-multilingual-2 (works with many languages)
• voyage-finance-2 (designed for financial documents)
• voyage-law-2 (optimized for legal text)

Key Features:

• Best-in-Class Performance: Beats OpenAI and other competitors in most tests and real-world use
• Domain-Specific Models: Special versions trained for specific industries like finance, law, and coding
• Long Text Support: Can handle much longer documents than most other providers
• Flexible Output Sizes: Choose from different output sizes to match your storage and speed needs
• Smart Cost Savings: Advanced technology that reduces storage costs by up to 200 times

Model Size & Output Dimensions:

• voyage-3-large: 1,024 dimensions (can use 256, 512, or 2,048)
• voyage-3.5: 1,024 dimensions with flexible sizing
• Maximum text length: 32,000 tokens

Pricing:

• voyage-3-large: $0.18 per million tokens
• voyage-3.5: $0.06 per million tokens
• voyage-3.5-lite: $0.02 per million tokens
• voyage-code-3: $0.18 per million tokens
• Free trial: 200 million tokens

3. Ollama: Local AI Models at Your Fingertips

Best for: Developers and businesses who prioritize data privacy and want to avoid ongoing cloud costs. Perfect for anyone who wants powerful AI tools without internet dependency or usage limits.

Ollama is an open-source platform that lets you run powerful AI models directly on your own computer without any internet connection. The project started in 2023 and quickly became the go-to solution for people who want to use AI privately and securely. 

You can find complete setup guides and model information on their official documentation. Ollama is completely free to download and use, with no subscription fees or hidden costs.

The platform makes it incredibly easy to download, run, and manage different AI models on your local machine. You keep full control over your data and never have to worry about sending sensitive information to cloud services.

Models Provided:

• nomic-embed-text (high-performance with long context support)
• mxbai-embed-large (state-of-the-art performance for large embeddings)
• all-minilm (efficient sentence-level embeddings)
• Any GGUF model from Hugging Face (thousands of options available)

Key Features:

• Complete Privacy Control: All AI processing happens on your computer so your data never leaves your device
• Zero Ongoing Costs: Download once and use forever with no subscription fees or usage limits
• Easy Local Setup: Simple installation process that works on Windows, Mac, and Linux computers
• No Internet Required: Run AI models completely offline once they are downloaded to your machine
• Huge Model Library: Access to thousands of open-source models including specialized embedding models
• Developer Friendly: Works perfectly with popular programming frameworks and tools

Model Size & Output Dimensions:

• nomic-embed-text: 1,024 dimensions, context length up to 8,192 tokens
• mxbai-embed-large: 1,024 dimensions, optimized for BERT-large performance
• all-minilm: 384 dimensions, efficient for sentence-level tasks
• Supports models ranging from small (384 dimensions) to very large (4,096+ dimensions)

Pricing:

• Completely free to download and use
• No subscription fees or usage limits
• No API costs or hidden charges
• Only cost is your own computer hardware
• All models available at zero cost

4. Cohere: Multilingual Text Understanding Made Simple

Best for: Companies that work with multiple languages or need reliable multilingual text processing. Great for businesses that want proven technology with good customer support.

Cohere builds embedding models that work well across many different languages. The company started in 2019 and focuses on making AI tools that businesses can actually use. 

Check their detailed pricing and model information to see all available options and costs. They put special attention on making models that understand different languages equally well.

Their team includes researchers who helped create some of the early transformer technology. Cohere serves both small startups and large enterprises with flexible pricing and deployment options.

Models Provided:

• embed-v4.0 (newest model with multimodal support)
• embed-multilingual-v3.0 (works with 100+ languages)
• embed-english-v3.0 (optimized for English only)
• embed-multilingual-light-v3.0 (faster multilingual processing)
• embed-english-light-v3.0 (faster English processing)

Key Features:

• Strong Multilingual Support: Works equally well with over 100 different languages from around the world
• Light Model Options: Faster versions available when you need quick results over maximum accuracy
• Enterprise Ready: Built for business use with security features and reliable performance
• Easy Integration: Simple to add to existing systems with good documentation and support
• Flexible Deployment: Can run on your servers, their cloud, or major cloud platforms

Model Size & Output Dimensions:

• embed-multilingual-v3.0: 1,024 dimensions
• embed-english-v3.0: 1,024 dimensions
• Light versions: 384 dimensions
• Maximum text length: 512 tokens

Pricing:

• embed-v4.0: $0.12 per million tokens
• Free trial available with rate limits
• Production pricing starts after trial period
• Volume discounts available for large users

5. Google (Gemini): Free and Powerful Text Embeddings

Best for: Developers who want high-quality embeddings without paying fees when just starting out. Perfect for startups, researchers, and anyone who needs reliable text processing on a budget.

Google provides embedding models through their Gemini platform that offer great performance without any cost. The company launched these models in 2025 as part of their broader AI strategy. 

You can find complete pricing details and free tier information in their official pricing guide. Google has decades of experience in text processing and search technology.

Their embedding models benefit from Google's massive research in language understanding. The company offers both free and paid tiers, making it accessible for projects of any size.

Models Provided:

• gemini-embedding-001 (newest and most capable model)
• text-embedding-004 (previous generation model)
• text-embedding-005 (latest research model)
• text-multilingual-embedding-002 (specialized for multiple languages)

Key Features:

• Completely Free Tier: Use Google AI Studio at no cost with generous limits for most projects
• Advanced Technology: Benefits from Google's latest research in language understanding and processing
• Adjustable Output Size: Can reduce dimensions to save storage while keeping good performance
• Strong Multilingual Performance: Works well across many languages with consistent quality
• Easy Google Integration: Works smoothly with other Google Cloud services and tools

Model Size & Output Dimensions:

• gemini-embedding-001: 3,072 dimensions (adjustable down to 768)
• text-embedding-004: 768 dimensions
• Maximum text length: 2,048 to 8,192 tokens depending on model

Pricing:

• Google AI Studio: Completely free with rate limits
• Gemini API free tier: Available for testing and small projects
• Paid tier: Available for higher usage limits
• Very competitive pricing compared to other providers

6. Jina AI: Open Source Innovation in Text Embeddings

Best for: Developers who want cutting-edge technology with open source flexibility. Great for companies that need long text processing or want to customize their embedding solution.

Jina AI creates powerful embedding models that you can use for free or through their paid service. The company started in 2020 and focuses on making advanced AI technology available to everyone. 

Visit their embedding platform to see pricing and get API access. They believe in open source development and share most of their work publicly.

Their latest models compete with the best commercial options while offering more flexibility. Jina AI has a strong community of developers who contribute to improving their models and tools.

Models Provided:

• jina-embeddings-v3 (multilingual with task-specific adapters)
• jina-embeddings-v4 (newest multimodal model)
• jina-embeddings-v2-base-en (English-focused model)
• jina-embeddings-v2-base-es (Spanish-English bilingual model)

Key Features:

• Task-Specific Optimization: Special adapters that make the model work better for different types of tasks
• Very Long Text Support: Can process documents up to 8,192 tokens without breaking them into pieces
• Multilingual Excellence: Works with 89+ languages and performs well across all of them
• Flexible Dimensions: Adjust output size from 32 to 1,024 dimensions based on your needs
• Open Source Option: Download and run models yourself or use their hosted service

Model Size & Output Dimensions:

• jina-embeddings-v3: 1,024 dimensions (adjustable down to 32)
• jina-embeddings-v4: 2,048 dimensions (adjustable down to 128)
• Maximum text length: 8,192 tokens

Pricing:

• 10 million free tokens for new users
• Token-based pricing after free tier
• Open source models available at no cost
• Self-hosting option to avoid API costs

7. Voyage AI Partnership (Anthropic): Safety-First Text Understanding

Best for: Companies that prioritize safety and reliability in their AI systems. Perfect for businesses that want the backing of a leading AI safety company.

Anthropic partners with Voyage AI to provide embedding services rather than creating their own models. Anthropic is the company behind Claude AI and focuses heavily on building safe and reliable AI systems. 

You can learn more about their embedding approach in their official embedding guide. They chose Voyage AI as their recommended partner after careful testing.

This partnership means you get Anthropic's commitment to safety and reliability combined with Voyage AI's technical excellence. Anthropic provides additional oversight to ensure the models work well for their users.

Models Provided:

• All Voyage AI models available through Anthropic's recommendation
• Focus on voyage-3 series for general use
• Domain-specific models for specialized applications

Key Features:

• Safety-First Approach: Models tested and approved by leading AI safety researchers
• Proven Reliability: Backed by Anthropic's reputation for building trustworthy AI systems
• Enterprise Grade: Designed to meet the needs of serious business applications
• Comprehensive Testing: Models undergo additional verification for quality and safety
• Expert Support: Access to both Voyage AI technical support and Anthropic guidance

Model Size & Output Dimensions:

• Same specifications as Voyage AI models
• voyage-3 series recommended for most applications
• Full range of dimension options available

Pricing:

• Standard Voyage AI pricing applies
• 200 million token free trial available
• Enterprise pricing options through Anthropic partnership

8. Amazon Web Services: Cloud-Native Embedding Solutions

Best for: Companies already using AWS services or those that need enterprise-grade security and scalability. Perfect for businesses that want managed AI services with guaranteed uptime.

AWS provides embedding models through their Bedrock platform and offers hosting for many third-party models. Amazon has been building cloud AI services since 2006 and has deep experience in scalable technology. 

Check their Bedrock pricing page for detailed costs and model options. Their platform serves millions of customers worldwide.

AWS focuses on making it easy for businesses to use AI without managing complex infrastructure. They offer both their own models and popular third-party options through a single platform.

Models Provided:

• Amazon Titan Text Embeddings (AWS native model)
• Cohere embeddings through Bedrock
• Various third-party models through marketplace
• Custom model hosting options

Key Features:

• Enterprise Security: Built-in security features that meet strict business and government requirements
• Scalable Infrastructure: Automatically handles high usage without performance issues
• AWS Integration: Works seamlessly with other Amazon services like databases and storage
• Managed Service: No need to worry about server maintenance or software updates
• Multiple Model Choice: Access to various embedding models through one platform

Model Size & Output Dimensions:

• Varies by specific model chosen
• Amazon Titan: 1,536 dimensions
• Full range of options through Bedrock marketplace

Pricing:

• AWS free tier available for testing
• Pay-per-use pricing for production
• Volume discounts for large usage
• Enterprise contracts available

9. Mistral AI: European Innovation in Text Processing

Best for: Companies that want high-quality European-developed AI technology. Great for businesses that need efficient models with strong performance across different languages.

Mistral AI creates high-performance embedding models from their base in France. The company started in 2023 by former researchers from major tech companies. 

Visit their technology page to learn about their models and pricing options. They focus on building efficient models that deliver excellent results without requiring massive computing resources.

Their approach emphasizes practical performance over theoretical benchmarks. Mistral AI has gained recognition for creating models that work well in real business applications while being cost-effective to run.

Models Provided:

• mistral-embed (general-purpose embedding model)
• Various specialized models for different use cases
• Open source options available

Key Features:

• High Accuracy Performance: Consistently ranks at the top in independent testing and benchmarks
• Efficient Processing: Designed to use less computing power while maintaining quality results
• European Standards: Built with European data privacy and AI regulations in mind
• Cost-Effective: Competitive pricing that provides good value for the performance level
• Open Development: Some models available as open source for flexibility

Model Size & Output Dimensions:

• Varies by specific model
• Optimized dimensions for different use cases
• Efficient size-to-performance ratio

Pricing:

• Competitive API-based pricing
• Volume discounts available
• Some open source options at no cost

10. Snowflake: Data Warehouse Native Embeddings

Best for: Companies that already store their data in Snowflake and want to add AI capabilities. Perfect for enterprises that need to process large amounts of data efficiently and securely.

Snowflake provides embedding capabilities directly within their data warehouse platform. The company has been a leader in cloud data services since 2012 and serves thousands of enterprises worldwide. 

Learn more about their AI capabilities on their Cortex platform page. Their approach integrates AI directly into where your data already lives.

This integration means you can create embeddings without moving data between different systems. Snowflake handles the computing and storage automatically as part of their managed service.

Models Provided:

• snowflake-arctic-embed-l-v2.0 (native Snowflake model)
• Cortex AI Functions (managed embedding service)
• Integration with external models

Key Features:

• Native Data Integration: Work with your data directly without copying or moving it to other systems
• Enterprise Security: Built-in security controls that meet strict compliance requirements
• SQL Interface: Use familiar database commands to create and work with embeddings
• Automatic Scaling: Handles large data processing jobs without manual setup or monitoring
• Cost Integration: Embedding costs included in your regular Snowflake billing

Model Size & Output Dimensions:

• Optimized for data warehouse use cases
• Various dimension options available
• Designed for processing large datasets efficiently

Pricing:

• Integrated with Snowflake compute pricing
• No separate AI service fees
• Pay based on compute usage
• Volume pricing available for large users

11. Hugging Face: Community-Driven AI Innovation

Best for: Developers who want access to the newest research models and open source flexibility. Perfect for companies that need specific model types or want to avoid vendor lock-in.

Hugging Face hosts the largest collection of open source embedding models in the world. The company started in 2016 and has become the main platform where AI researchers share their work. 

Check their pricing page for hosted service options, though most models are free to download. They make advanced AI technology accessible to everyone through their community platform.

Their platform includes thousands of different embedding models created by researchers and companies worldwide. This gives you more choices than any other provider and access to the latest research developments.

Models Provided:

• sentence-transformers models (hundreds of options)
• Community-contributed embedding models
• Research models from universities and labs
• Popular models from major companies

Key Features:

• Huge Model Selection: Access to thousands of different embedding models for every possible use case
• Community Innovation: New models added regularly by researchers and developers worldwide
• Open Source Freedom: Download and modify models without restrictions or ongoing fees
• Easy Local Deployment: Run models on your own servers with simple installation
• Research Access: Get early access to cutting-edge models before they become commercial

Model Size & Output Dimensions:

• Wide variety of sizes from tiny to very large
• Dimensions range from 128 to 4,096+
• Models optimized for different use cases and languages

Pricing:

• Most models completely free to download and use
• Optional paid inference endpoints for convenience
• Pro subscriptions for additional features
• Self-hosting costs only what you pay for servers

12. E5 (Microsoft): Open Source Enterprise Quality

Best for: Companies that want enterprise-quality models without ongoing costs. Great for organizations that need to run models on their own infrastructure or want full control over their AI systems.

Microsoft's E5 models provide enterprise-quality embeddings as open source software. Microsoft Research created these models to advance the state of text understanding technology. 

You can access all E5 models and documentation through their Hugging Face collection. They released the models publicly to help the entire AI community benefit from their research.

The E5 series represents some of the most advanced open source embedding technology. These models compete with the best commercial options while being completely free to use and modify.

Models Provided:

• e5-mistral-7b-instruct (large, high-performance model)
• e5-large-v2 (balanced size and performance)
• multilingual-e5-large-instruct (multilingual version)
• Various smaller E5 models for different needs

Key Features:

• Enterprise Quality: Performance comparable to expensive commercial models at no cost
• Large Model Options: Some of the biggest open source embedding models available
• Microsoft Research: Built by one of the world's leading AI research teams
• Full Customization: Modify and fine-tune models for your specific needs
• No Vendor Lock-in: Complete independence from any commercial AI provider

Model Size & Output Dimensions:

• e5-mistral: 4,096 dimensions
• e5-large-v2: 1,024 dimensions
• Various sizes available for different performance needs

Pricing:

• Completely free to download and use
• No API fees or usage limits
• Only costs are your own server expenses
• No licensing fees for commercial use

13. BGE (Beijing Academy of AI): Chinese Innovation in Text Understanding

Best for: Companies working with Chinese language content or those that want high-quality open source models. Perfect for global businesses that need strong multilingual performance without licensing costs.

BGE models come from the Beijing Academy of Artificial Intelligence and represent some of the best open source embedding technology from China. The academy focuses on advancing AI research and making their discoveries available to everyone worldwide. 

Access all BGE models through their official Hugging Face page. The BGE series has gained recognition for achieving commercial-quality results while remaining completely free.

Their models perform exceptionally well on both English and Chinese text, making them valuable for global applications.

Models Provided:

• bge-large-en-v1.5 (English-optimized large model)
• bge-m3 (multilingual model with strong Chinese support)
• bge-small-en-v1.5 (smaller English model)
• Various specialized BGE models

Key Features:

• Strong Chinese Language Support: Best-in-class performance for Chinese text processing and understanding
• Multilingual Excellence: Works well across many languages while maintaining high quality
• Academic Research Quality: Built by leading researchers with focus on advancing the field
• Completely Open Source: Free to use, modify, and distribute without any restrictions
• Competitive Performance: Matches or beats many commercial models in testing

Model Size & Output Dimensions:

• Various dimension options from 384 to 1,024
• Multiple model sizes for different performance needs
• Optimized for both English and Chinese processing

Pricing:

• Completely free for all uses
• No API costs or usage restrictions
• Open source license allows commercial use
• Only costs are your own infrastructure

What are Embedding models?

Embedding models can turn words and text into numbers that AI models can easily understand. Think of them as translators that convert human language into a special number code that captures the true meaning behind the words.

When you feed text into an embedding model, it creates a long list of numbers called a vector. Each piece of text gets its own unique number pattern. The texts with similar meanings get similar number patterns, while completely different topics get very different patterns.

This number translation helps AI models do different tasks with text. They can find similar documents, search for information based on meaning rather than just matching words, and understand what you really want when you ask questions.

Key Benefits:

• Better Search: Find information by meaning, not just word matching
• Smart Comparisons: Automatically group similar content together
• Language Understanding: Help computers grasp what text actually means
• Fast Processing: Computers work much faster with numbers than words
• Accurate Results: Get more relevant answers to your questions

Conclusion

Embedding models have become essential tools for making AI understand and work with text in meaningful ways. As Dharmesh Shah explained, these models solve critical problems by helping AI access and process private documents that weren't part of their original training.

All 13 embedding models offer a different range of features. Some offer top-of-the-line embedding models, some offer no-API-cost embedding models, and some offer multilingual embedding models. Choose according to your preferences.

However, as Shah noted, most solutions require significant technical expertise to set up properly. The complexity of connecting APIs, managing vector databases, and configuring embeddings can be overwhelming for non-technical users.

For those seeking a simpler path, tools like Elephas eliminate this technical barrier entirely. With zero setup complexity, you can upload documents, connect your favorite PKM tools like Notion and Obsidian, and start chatting with your knowledge base immediately—all while automating repetitive tasks through intelligent workflows.

Try Elepahs for free