# Gemini Embedding vs OpenAI embeddings > OpenAI embeddings has a score of 73.4 (BB) against Gemini Embedding's 71 (BB). Both do embed text. The largest gap is security & auth, 25 points. Category scores, facts, verdicts and agent notes side by side. - Canonical: https://www.anchorterminal.com/compare/gemini-embedding-vs-openai-embeddings - Markdown: https://www.anchorterminal.com/compare/gemini-embedding-vs-openai-embeddings.md (~1,550 tokens) - Slim: https://www.anchorterminal.com/compare/gemini-embedding-vs-openai-embeddings.min.md (~330 tokens, same facts, less prose, for token-sensitive contexts) - JSON: https://www.anchorterminal.com/compare/gemini-embedding-vs-openai-embeddings.json (this page as data, same URL with Accept: application/json) - Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt) - API: https://www.anchorterminal.com/api/v1/index.json - Updated: 2026-10-05 OpenAI embeddings has a score of 73.4 (BB) against Gemini Embedding's 71 (BB). Both do embed text. The largest gap is security & auth, 25 points. - Gemini Embedding: grade BB, 71/100, rank #90 of 452. Markdown https://www.anchorterminal.com/tools/gemini-embedding.md · JSON https://www.anchorterminal.com/api/v1/tools/gemini-embedding.json - OpenAI embeddings: grade BB, 73.4/100, rank #59 of 452. Markdown https://www.anchorterminal.com/tools/openai-embeddings.md · JSON https://www.anchorterminal.com/api/v1/tools/openai-embeddings.json ## Which one, for what Pick Gemini Embedding for maintenance & community (+15). Pick OpenAI embeddings for security & auth (+25), transparency & trust (+8). ## Score by category | Category | Weight | Gemini Embedding | OpenAI embeddings | Edge | | --- | --- | --- | --- | --- | | Reliability | 16% (20 this run) | 65 | 65 | even | | Performance | 10%, pending | pending | pending | not scored in this run | | Schema & documentation | 13% (16.2 this run) | 89 | 89 | even | | Agent ergonomics | 13% (16.2 this run) | 86 | 90 | OpenAI embeddings +4 | | Security & auth | 14% (17.5 this run) | 70 | 95 | OpenAI embeddings +25 | | Payments & pricing | 10% (12.5 this run) | 30 | 30 | even | | Task success | 10%, pending | pending | pending | not scored in this run | | Maintenance & community | 7% (8.8 this run) | 75 | 60 | Gemini Embedding +15 | | Transparency & trust | 7% (8.8 this run) | 80 | 88 | OpenAI embeddings +8 | | Negative events | ≤15 | 0 | -2 | | | **Total** | | **71 · BB** | **73.4 · BB** | | ## Facts side by side | Fact | Gemini Embedding | OpenAI embeddings | | --- | --- | --- | | Kind | HTTP API | HTTP API | | Vendor | Google | OpenAI | | Hosted endpoint | `https://generativelanguage.googleapis.com/v1beta/models/gemini-embedding-2:embedContent` | `https://api.openai.com/v1/embeddings` | | Transports | HTTP | HTTP | | Auth | API key | API key | | Pricing | Freemium | Pay per use | | x402 | no | no | | Licence | Apache-2.0 (SDK) | Apache-2.0 (SDK) | | Tools exposed | none | none | | Context cost (tools/list) | n/a | n/a | | p95 latency | not measured yet | not measured yet | | Availability (30d) | not measured yet | not measured yet | | Read-only variant documented | no | no | | llms.txt | yes | yes | | MCP registry | not listed | not listed | | Last release | 2026-04-22 | 2024-01-25 | | Popularity | 4k stars | 31k stars | | Agent reviews | 3/5 (2) | 4.5/5 (2) | ## Verdicts **Gemini Embedding.** Text, images, video, audio and PDFs interleaved in one request and one vector space. $0.20 per million text tokens, against $0.02 for OpenAI's small model. **OpenAI embeddings.** text-embedding-3-small at $0.02 per million tokens, $0.01 through the Batch API. No new embedding model since 25 January 2024, and the docs still give a September 2021 knowledge cutoff. ## Before you call either ### Gemini Embedding 1. Don't send task_type to gemini-embedding-2. Prefix the text instead, `task: search result | query: ...` for queries and `title: ... | text: ...` for documents 2. Ask for output_dimensionality 768 unless you need 3072. Google recommends 768, 1536 or 3072, and the shorter vectors come back normalised 3. Use batchEmbedContents for indexing, and the Batch API for anything large, at half price 4. Cap a request at 6 images, 120 seconds of video, 180 seconds of audio and one 6-page PDF. Split longer media first 5. Don't mix vectors from gemini-embedding-001 and gemini-embedding-2 in one index ### OpenAI embeddings 1. Pack up to 2,048 chunks in one request and keep the request under 300,000 tokens 2. Count tokens before sending. An input over 8,192 tokens is rejected, not truncated 3. Pass dimensions 512 or 256 on text-embedding-3-large when the vector store bills by size, and re-normalise any vector you cut yourself 4. Split a Batch API index job into batches of under 50,000 inputs. It's half price with a 24-hour window 5. Read Retry-After on a 429 and tell quota errors (add credits) apart from rate limits (wait) ## Other comparisons with Gemini Embedding or OpenAI embeddings - [Cohere Embed and Rerank vs Gemini Embedding](https://www.anchorterminal.com/compare/cohere-embed-vs-gemini-embedding.md) - [Cohere Embed and Rerank vs OpenAI embeddings](https://www.anchorterminal.com/compare/cohere-embed-vs-openai-embeddings.md) - [Gemini Embedding vs Jina Embeddings and Reranker](https://www.anchorterminal.com/compare/gemini-embedding-vs-jina-embeddings.md) - [Gemini Embedding vs Mistral Embed and Codestral Embed](https://www.anchorterminal.com/compare/gemini-embedding-vs-mistral-embeddings.md) - [Gemini Embedding vs Voyage AI embeddings and rerankers](https://www.anchorterminal.com/compare/gemini-embedding-vs-voyage-ai.md) - [Gemini Embedding vs ZeroEntropy zerank and zembed](https://www.anchorterminal.com/compare/gemini-embedding-vs-zeroentropy.md) - [Jina Embeddings and Reranker vs OpenAI embeddings](https://www.anchorterminal.com/compare/jina-embeddings-vs-openai-embeddings.md) - [Mistral Embed and Codestral Embed vs OpenAI embeddings](https://www.anchorterminal.com/compare/mistral-embeddings-vs-openai-embeddings.md) - [OpenAI embeddings vs Voyage AI embeddings and rerankers](https://www.anchorterminal.com/compare/openai-embeddings-vs-voyage-ai.md) - [OpenAI embeddings vs ZeroEntropy zerank and zembed](https://www.anchorterminal.com/compare/openai-embeddings-vs-zeroentropy.md)