Embeddings API Pricing 2026: Add RAG & Knowledge Bases to Your App on a Budget

Embeddings API Pricing 2026: Add RAG & Knowledge Bases to Your App on a Budget#

Embeddings API pricing in 2026 ranges from $0.02–$0.20 per 1M tokens depending on the provider, with OpenAI offering $5 free credits for new users and cheaper alternatives like Gemini 3.1 Pro at $2 per 1M input tokens. For indie developers, startups, and product teams adding retrieval-augmented generation (RAG) or knowledge bases to apps, choosing the right embeddings provider can cut infrastructure costs by 60–80% while maintaining production-grade quality.

Key Takeaways#

• OpenAI embeddings cost $0.02–$0.10 per 1M tokens; new users get $5 free credits (~250M tokens)
• Gemini 3.1 Pro embeddings start at $2 per 1M input tokens, making it the cheapest major option for high-volume use
• Claude embeddings via Anthropic cost $5 per 1M input tokens but excel at semantic search and domain-specific RAG
• IntelliVerse-X AI Gateway bundles all LLM and embedding models under one API key at $0.24/M tokens for chat, with unified billing and no vendor lock-in
• RAG + knowledge bases typically cost $50–$500/month for indie apps; embedding costs are 10–30% of total LLM spend

What Are Embeddings and Why They Cost Money#

Embeddings convert text into numerical vectors that AI models use to understand semantic meaning. When you build a knowledge base or RAG system, you embed documents once, then query them repeatedly—making embeddings a core cost driver for chatbots, customer support bots, and search features.

Every time you: - Upload a document to a knowledge base - Index a webpage for semantic search - Sync user chat history for memory

...you're paying for embeddings tokens. OpenAI's embeddings API charges per 1M tokens processed, and costs scale linearly with your app's data volume and user base.

Embeddings API Pricing Breakdown by Provider (2026)#

OpenAI Embeddings: Best for Production Apps

OpenAI's embeddings pricing is tiered by model:

• text-embedding-3-small: $0.02 per 1M tokens (fast, lightweight)
• text-embedding-3-large: $0.10 per 1M tokens (higher quality, semantic depth)

Real cost example: Embedding a 10,000-word knowledge base (≈13M tokens) with text-embedding-3-small costs ~$0.26. Querying that base 1,000 times/month adds ~$0.02.

New user bonus: OpenAI offers $5 free credits for new accounts—enough to embed ~250M tokens risk-free.

Gemini 3.1 Pro: Cheapest High-Volume Option

According to June 2026 LLM pricing comparisons, Google's Gemini 3.1 Pro embeddings cost:

• Input: $2 per 1M tokens
• Output: $12 per 1M tokens

For embedding-only workloads (no output tokens), Gemini is 100× cheaper than Claude and 200× cheaper than OpenAI's large model. Best for indie developers embedding massive document collections.

Claude Embeddings: Premium Semantic Quality

Anthropic's Claude embeddings cost $5 per 1M input tokens. While pricier, Claude excels at: - Domain-specific RAG (legal, medical, technical docs) - Multi-language semantic search - Nuanced context understanding

Justified for apps where search quality directly impacts revenue or user retention.

Real-World Cost Scenarios for Indie Apps#

Scenario 1: Customer Support Chatbot (Small SaaS)

Setup: 50,000 support docs, 1,000 user queries/month

• Initial embedding (text-embedding-3-small): 50M tokens × $0.02 = $1.00
• Monthly queries (1M tokens): $0.02
• Total monthly: ~$0.03 (after first month)

Scenario 2: Game Studio Knowledge Base (Medium Studio)

Setup: 200,000 game design docs, 10,000 internal queries/month, 50,000 player queries/month

• Initial embedding (text-embedding-3-large): 250M tokens × $0.10 = $25.00
• Monthly queries (60M tokens): $6.00
• Total monthly: ~$6.00 (after first month)

Scenario 3: Content Studio RAG (High Volume)

Setup: 1M articles, 500,000 queries/month

• Initial embedding (Gemini): 1B tokens × $2 = $2,000 (or $10 with OpenAI small model)
• Monthly queries (500M tokens): $1,000 (Gemini) or $10 (OpenAI small)
• Total monthly: ~$1,000 (Gemini) or ~$10 (OpenAI small)

*Note: Gemini shines at ultra-high volumes; OpenAI dominates for balanced quality + cost.*

How to Reduce Embeddings Costs by 60–80%#

1. Use Smaller Embedding Models for High Volume

Switch from text-embedding-3-large ($0.10) to text-embedding-3-small ($0.02) if semantic quality permits. OpenAI benchmarks show small models perform within 5–10% of large for most use cases.

2. Batch Embed Once, Query Many Times

Embed documents during off-peak hours, cache results, then serve queries from vector databases (Pinecone, Weaviate, Milvus). This separates expensive embedding costs from cheap retrieval.

3. Implement Semantic Caching

Cache embeddings for frequently asked questions. If a user asks "How do I reset my password?" 1,000 times/month, embed it once and reuse the vector.

4. Use IntelliVerse-X AI Gateway for Unified Billing

IntelliVerse-X's AI Gateway bundles OpenAI, Claude, Gemini, DeepSeek, and Qwen embeddings under one API key at $0.24/M tokens for chat (embeddings included). Benefits:

• No vendor lock-in: Switch providers mid-request
• One invoice: Consolidate all LLM and embedding spend
• Built-in RAG: Knowledge bases and user memory on cheap embeddings
• Fallback routing: If OpenAI rate-limits, auto-route to Claude or Gemini

5. Prune and Archive Old Documents

Re-embed only active, high-relevance documents. Archive seasonal content (holiday guides, event-specific FAQs) to reduce monthly token spend by 20–40%.

Frequently Asked Questions#

Q: How many tokens are in a typical document?

A: A 1,000-word article ≈ 1,300 tokens. A 10-page PDF ≈ 13,000 tokens. OpenAI's tokenizer lets you count exact tokens before embedding.

Q: Is embedding cost or LLM cost the bigger expense?

A: For RAG apps, embeddings are 10–30% of total spend. LLM completion tokens (generating responses) typically cost 3–5× more. Optimize both: use small embedding models + shorter LLM prompts.

Q: Can I use free embedding models?

A: Open-source models (Sentence-Transformers, JINA) run locally for free but require GPU infrastructure ($50–$500/month). For indie apps, paid APIs ($0.02–$5/M tokens) are cheaper than self-hosting below 100M monthly tokens.

Sources#

• OpenAI Embeddings API Pricing Calculator
• OpenAI API Pricing Overview
• LLM API Providers Pricing Comparison 2026
• Anthropic Claude API Pricing

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Get Started with Embeddings Today#

Ready to add RAG or a knowledge base to your app without breaking the budget? **Get an IntelliVerse-X AI Gateway API key** and start embedding for $0.24/M tokens—with unified access to OpenAI, Claude, Gemini, and more.

Need a custom setup? **Book a free 30-minute consultation** with our team to design a cost-optimized embeddings strategy for your game, app, or studio.