Embeddings API Pricing 2026: Complete Cost Breakdown for App Developers

Embeddings API Pricing 2026: Complete Cost Breakdown for App Developers#

OpenAI's text-embedding-3-small costs $0.02 per 1M tokens, while Gemini Embedding 2 runs $0.20 per 1M tokens standard or $0.10 with batch processing—making batch embedding the fastest way to cut costs 50% for indie studios and startups building RAG systems, chatbots, or knowledge bases into their products.

Key Takeaways#

• OpenAI embeddings are cheapest at scale: text-embedding-3-small ($0.02/1M tokens) beats Gemini ($0.20/1M) and Claude ($0.10/1M) for high-volume embedding workloads
• Batch processing cuts costs in half: Gemini's batch API drops embedding costs from $0.20 to $0.10 per 1M tokens; OpenAI's batch endpoint offers similar savings
• Free tier credits offset startup costs: OpenAI provides $5 free credits for new users (~250M tokens embeddable)
• RAG + knowledge bases are the biggest cost drivers: storing 100K documents at 500 tokens each = 50M tokens ($1–$10 depending on provider)
• IntelliVerse-X AI Gateway offers unified pricing: single API key across all LLMs, embeddings, and video/image models at $0.24/M tokens for chat—undercut OpenAI's GPT-4o by 60%

What Are Embeddings and Why Do They Cost Money?#

Embeddings convert text into numerical vectors that AI models use for semantic search, similarity matching, and retrieval-augmented generation (RAG). When you build a chatbot with memory, add a knowledge base to your game, or index customer support docs for search, you're paying per token embedded—not per query.

For example, a 500-token document costs $0.01 to embed once with OpenAI's cheapest model. Store 100,000 documents? That's 50M tokens = $1 upfront. Add 10K new docs monthly? Another $0.20/month in embedding costs alone.

Embeddings API Pricing Comparison: October 2026#

OpenAI Text Embeddings

| Model | Input Cost | Cached Input | Best For | |-------|-----------|--------------|----------| | text-embedding-3-small | $0.02/1M tokens | N/A | RAG, chatbot memory, budget-conscious teams | | text-embedding-3-large | $0.13/1M tokens | N/A | High-accuracy semantic search, production |

Free tier: New OpenAI users get $5 credits, enough to embed ~250M tokens.

Google Gemini Embeddings

| Model | Standard Cost | Batch Cost | Best For | |-------|---------------|-----------|----------| | Embedding 2 | $0.20/1M tokens | $0.10/1M tokens | Multimodal (text + image), cost-optimized batch jobs |

Batch savings: Process embeddings asynchronously and cut costs 50%. Ideal for overnight knowledge base updates.

Anthropic Claude

Claude does not offer a standalone embeddings API. Instead, use Claude's native context window (200K tokens) for in-prompt search, or pair Claude with OpenAI/Gemini embeddings for hybrid RAG.

Real-World Cost Examples for US App Developers#

Scenario 1: Indie Game Studio (Discord Bot with Memory)

• Use case: Store player chat history (20K messages/month, 100 tokens avg)
• Monthly embedding cost: 2M tokens × $0.02 (OpenAI) = $0.04
• Best choice: OpenAI text-embedding-3-small
• Annual cost: ~$0.50 (negligible)

Scenario 2: Startup (Customer Support Chatbot)

• Use case: Index 50K support docs (500 tokens avg), embed 1K new docs/month
• Initial embedding: 50M tokens × $0.02 = $1.00
• Monthly new embeddings: 500K tokens × $0.02 = $0.01
• Best choice: OpenAI text-embedding-3-small
• Annual cost: ~$1.12

Scenario 3: Content Studio (RAG Pipeline for Video Scripts)

• Use case: Embed 100K video transcripts (2K tokens avg), process 5K new transcripts/month
• Initial embedding: 200M tokens × $0.02 (OpenAI) or $0.20 (Gemini) = $4.00 or $40
• Monthly new embeddings: 10M tokens × $0.02 = $0.20
• Batch optimization: Use Gemini batch at $0.10/1M = $1.00/month (saves $30/month vs. standard)
• Best choice: Gemini Embedding 2 with batch processing
• Annual cost: $1 (init) + $12 (monthly batch) = ~$13

How to Reduce Embeddings API Costs by 50%#

1. Use Batch Processing

Gemini's batch API and OpenAI's batch endpoint process embeddings asynchronously, cutting costs in half. Ideal for:

• Nightly knowledge base updates
• Monthly document indexing
• One-time data migrations

Setup time: 15 minutes. Savings: 50% on embedding costs.

2. Choose the Right Model

• Small/cheap: OpenAI text-embedding-3-small ($0.02/1M) for RAG, search, similarity
• Large/accurate: OpenAI text-embedding-3-large ($0.13/1M) only if semantic precision is critical
• Multimodal: Gemini Embedding 2 ($0.20/1M standard, $0.10 batch) if indexing images + text

3. Embed Once, Reuse Forever

Store embeddings in a vector database (Pinecone, Weaviate, Supabase pgvector) after the first embedding. Never re-embed the same doc.

4. Consolidate Embeddings Across Apps

Use a unified API gateway like IntelliVerse-X AI Gateway to route all embeddings through one key—track usage, negotiate volume discounts, and avoid vendor lock-in.

When to Use Batch Embeddings vs. Real-Time#

Use Real-Time Embeddings ($0.02–$0.20/1M)

• User uploads a doc to your app → embed instantly for immediate search
• Chatbot ingests user query → embed for live RAG lookup
• A/B testing new content → embed on-demand

Use Batch Embeddings ($0.01–$0.10/1M)

• Nightly sync of 10K support docs
• Weekly knowledge base refresh
• One-time migration of 100K legacy documents
• Monthly content ingestion pipeline

Cost difference: Processing 100M tokens batch vs. real-time = $2 saved (50% discount).

IntelliVerse-X AI Gateway: Unified Embeddings + LLM Pricing#

Instead of juggling OpenAI, Gemini, and Claude APIs separately, IntelliVerse-X AI Gateway offers:

• Single API key for embeddings, LLMs, video, image, 3D, and avatar models
• Unified pricing: Chat from $0.24/M tokens (60% cheaper than OpenAI GPT-4o)
• Built-in RAG: Knowledge bases and user memory on cheap embeddings
• No vendor lock-in: Switch models mid-request without code changes
• Free tier: Start building with $5 credits

Example: Embed 100M tokens + run 1M chat completions = $2.40 (vs. $5+ with OpenAI alone).

Frequently Asked Questions#

Q: Do I pay per embedding or per token?

You pay per token embedded, not per embedding request. A 500-token document = 500 tokens charged. OpenAI's pricing and Gemini's pricing both use token-level billing.

Q: Can I cache embeddings to avoid re-paying?

Yes. Store embeddings in a vector database after the first embedding—you never re-embed the same document. Costs are one-time per unique doc. For dynamic content (daily updates), embed only new/changed docs.

Q: Which embeddings API is best for a startup on a tight budget?

OpenAI text-embedding-3-small at $0.02/1M tokens is the cheapest option for most use cases. Use Gemini batch processing ($0.10/1M) if you can wait 24 hours and need to cut costs further. For unified pricing across LLMs + embeddings, IntelliVerse-X AI Gateway undercuts both at $0.24/M for chat + embeddings combined.

Sources#

• OpenAI API Pricing
• How Much Do AI APIs Cost? A 2026 Pricing Guide - G2
• OpenAI Embeddings Pricing Calculator & Cost Guide - CostGoat
• Google Gemini API Pricing Documentation
• Anthropic Claude API Pricing

---

Ready to Cut Your Embeddings Costs?#

Get started with IntelliVerse-X AI Gateway today:

• Get an API key: intelli-verse-x.ai/gateway — Chat from $0.24/M tokens, unified embeddings + LLM pricing
• Book a free 30-min consult: intelli-verse-x.ai/book-call — Our team will audit your current API spend and show you how to save 40–60% on embeddings + LLMs

Whether you're building a game with AI memory, a startup knowledge base, or a content studio RAG pipeline, IntelliVerse-X makes embeddings affordable at scale.