{ "data": { "a": { "slug": "openai-embeddings", "name": "OpenAI embeddings", "vendor": "OpenAI", "vendorUrl": "https://developers.openai.com", "kind": "http-api", "category": "embeddings", "summary": "OpenAI's text embedding API, with adjustable output dimensions for search and retrieval applications.", "url": "https://www.anchorterminal.com/tools/openai-embeddings", "markdownUrl": "https://www.anchorterminal.com/tools/openai-embeddings.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/openai-embeddings.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/openai-embeddings.json", "repo": "https://github.com/openai/openai-python", "license": "Apache-2.0 (SDK)", "transports": [ "http" ], "remoteUrl": "https://api.openai.com/v1/embeddings", "packages": [ { "registry": "pypi", "name": "openai" }, { "registry": "npm", "name": "openai" } ], "auth": "api-key", "authNotes": "`Authorization: Bearer` with a project key from the OpenAI platform. Same key and account as the rest of the OpenAI API.", "pricing": "usage", "pricingNotes": "text-embedding-3-small $0.02 and text-embedding-3-large $0.13 per million input tokens. No output charge. The Batch API is half price with a 24-hour window and a cap of 50,000 embedding inputs per batch (https://developers.openai.com/api/docs/models/text-embedding-3-large, https://developers.openai.com/api/docs/guides/batch). Prepaid credits, $5 minimum, shared with the rest of the API.", "priceSummary": "Pay per use", "where": "hosted", "x402": { "level": "no", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 31300, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-09-30" }, "docsUrl": "https://developers.openai.com/api/docs/guides/embeddings", "llmsTxt": "https://developers.openai.com/llms.txt", "openapi": "https://github.com/openai/openai-openapi", "capabilities": [ "embed.text", "embed.multilingual" ], "tags": [ "official", "hosted", "card-required", "openapi", "llms-txt", "python", "typescript", "batch", "closed-source" ], "lastRelease": "2024-01-25", "graded": true, "anchor": { "graded": true, "score": 73.4, "grade": "BB", "agentReady": true, "rank": 59, "ranked": true, "rankOf": 452, "categoryRank": 1, "methodology": "0.3", "run": "2026-10-01", "scores": { "ergonomics": 90, "maintenance": 60, "payments": 30, "reliability": 65, "schema": 89, "security": 95, "transparency": 88 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "high", "date": "2026-10-01" }, "negative": -2, "negativeNotes": [ "A breach at Mixpanel, OpenAI's analytics vendor, began on 2025-11-09 and was reported to OpenAI on 2025-11-25. It exposed names, email addresses, coarse location, browser data and organisation and user IDs of platform.openai.com users, but no API keys, API requests or usage data. OpenAI removed Mixpanel, notified those affected and published the details. Fixed and documented, so a small, decayed deduction (-2). https://openai.com/index/mixpanel-incident/" ], "verdict": "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.", "strengths": [ "text-embedding-3-small at $0.02 per million tokens, $0.01 through the Batch API", "Restricted project keys are set per endpoint, so an agent's key can be cut down to read and model calls", "Up to 2,048 inputs and 300,000 tokens in one request", "OpenAPI document, llms.txt and a dated changelog shared with the rest of the OpenAI API", "No training on API data by default, six months' notice before a GA model is retired" ], "weaknesses": [ "No new embedding model since 25 January 2024, and the docs still give a September 2021 knowledge cutoff", "Text only, 8,192 tokens an input, and no reranker", "Over-long inputs fail rather than being truncated, and output is float or base64 only", "A free tier is listed, but credits are prepaid after adding payment details, and nothing confirms a start without a card", "Elevated errors across the API including Embeddings on 17 and 29 September 2026, for about 1.5 and 5.4 hours" ], "agentNotes": [ "Pack up to 2,048 chunks in one request and keep the request under 300,000 tokens", "Count tokens before sending. An input over 8,192 tokens is rejected, not truncated", "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", "Split a Batch API index job into batches of under 50,000 inputs. It's half price with a 24-hour window", "Read Retry-After on a 429 and tell quota errors (add credits) apart from rate limits (wait)" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 2, "avgRating": 4.5, "history": [ { "basis": "public evidence", "confidence": "high", "grade": "BB", "methodology": "0.3", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 73.4 } ], "editorialScores": { "ergonomics": 90, "maintenance": 60, "payments": 30, "reliability": 65, "schema": 89, "security": 95, "transparency": 75 }, "provenanceScore": 100 }, "connect": { "install": "pip install openai # or: npm i openai", "http": "curl https://api.openai.com/v1/embeddings \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" -H \"content-type: application/json\" \\\n -d '{\"model\":\"text-embedding-3-small\",\"input\":[\"What does the embeddings endpoint return?\"],\"dimensions\":512}'" }, "letme": { "capability": "https://letme.dev/embed.text", "tool": "https://letme.dev/openai-embeddings" }, "sameCompany": [ "openai-api", "openai-moderation", "openai-image-api", "openai-sora", "openai-agents-sdk", "openai-codex" ], "area": "models", "unitPrices": [ { "item": "text-embedding-3-small", "unit": "1m-tokens", "usd": 0.02 }, { "item": "text-embedding-3-large", "unit": "1m-tokens", "usd": 0.13 }, { "item": "text-embedding-3-small, Batch API", "unit": "1m-tokens", "usd": 0.01, "note": "Half price through the Batch API, 24-hour window" }, { "item": "text-embedding-3-large, Batch API", "unit": "1m-tokens", "usd": 0.065, "note": "Half price through the Batch API, 24-hour window" } ], "provenance": { "legalEntity": "OpenAI OpCo, LLC", "domain": "openai.com", "domainRegistered": "2007-01-19", "domainNote": "openai.com was registered in 2007, before OpenAI existed.", "endpointOnVendorDomain": true, "terms": "https://openai.com/policies/services-agreement/", "privacy": "https://openai.com/policies/privacy-policy/", "statusPage": "https://status.openai.com", "changelog": "https://developers.openai.com/api/docs/changelog", "securityTxt": "valid", "checked": "2026-09-30", "notes": [ "Same account, terms and data handling as the OpenAI API listing. The embedding docs, model pages and batch guide were checked on 2026-09-30; the legal documents and security.txt are as checked for that listing.", "The docs pages are on developers.openai.com while the endpoint stays on api.openai.com." ], "score": 100 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/openai-embeddings.json", "live": { "slug": "openai-embeddings", "probe": { "target": "https://api.openai.com/v1/embeddings", "method": "get", "lastAt": "2026-10-05T03:17:30.083419058Z", "lastOk": true, "lastStatus": 401, "lastMs": 50, "lastNote": "asks for credentials", "authRequired": true, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 112, "p95ms24h": 178, "samples24h": 273, "samples30d": 938, "days": [ { "date": "2026-10-01", "probes": 109, "ok": 109 }, { "date": "2026-10-02", "probes": 248, "ok": 248 }, { "date": "2026-10-03", "probes": 271, "ok": 271 }, { "date": "2026-10-04", "probes": 272, "ok": 272 }, { "date": "2026-10-05", "probes": 38, "ok": 38 } ] }, "vendorStatus": { "page": "https://status.openai.com", "indicator": "none", "summary": "All Systems Operational", "checkedAt": "2026-10-05T03:19:09.686490393Z" }, "versions": [ { "registry": "github", "name": "openai/openai-python", "version": "v3.24.0", "released": "2026-10-02", "seenAt": "2026-10-04T16:35:31.371334587Z" }, { "registry": "npm", "name": "openai", "version": "7.27.0", "seenAt": "2026-10-04T16:35:31.320816589Z" }, { "registry": "pypi", "name": "openai", "version": "3.24.0", "released": "2026-10-02", "seenAt": "2026-10-04T16:35:31.204685983Z" } ], "githubStars": 31742, "npmWeekly": 50351921, "pypiWeekly": 72949998, "securityTxt": { "url": "https://openai.com/.well-known/security.txt", "state": "valid", "checkedAt": "2026-10-04T15:15:58.86463118Z" }, "llmsTxt": { "url": "https://developers.openai.com/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-10-04T15:18:06.146857182Z" }, "domain": { "domain": "openai.com", "registered": "2007-01-19", "source": "https://rdap.verisign.com/com/v1/domain/openai.com", "checkedAt": "2026-10-04T13:05:02.32020521Z" }, "updatedAt": "2026-10-05T03:19:09.686490393Z" } }, "b": { "slug": "zeroentropy", "name": "ZeroEntropy zerank and zembed", "vendor": "ZeroEntropy", "vendorUrl": "https://www.zeroentropy.dev", "kind": "http-api", "category": "embeddings", "summary": "Discontinued retrieval API acquired by Notion. Its embedding and reranking models remain available as open weights for self-hosting.", "url": "https://www.anchorterminal.com/tools/zeroentropy", "markdownUrl": "https://www.anchorterminal.com/tools/zeroentropy.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/zeroentropy.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/zeroentropy.json", "repo": "https://github.com/zeroentropy-ai/zeroentropy-python", "license": "Apache-2.0 (SDKs and model weights)", "transports": [ "http" ], "remoteUrl": "https://api.zeroentropy.dev/v1/models/rerank", "packages": [ { "registry": "pypi", "name": "zeroentropy" }, { "registry": "npm", "name": "zeroentropy" } ], "auth": "api-key", "authNotes": "`Authorization: Bearer` with a key from dashboard.zeroentropy.dev. The SDKs read `ZEROENTROPY_API_KEY`. An EU endpoint at eu-api.zeroentropy.dev takes the same key.", "pricing": "usage", "pricingNotes": "No longer for sale. The API was supported until 2026-09-04 and new signups closed on 2026-07-24 (https://www.zeroentropy.dev/articles/zeroentropy-is-joining-notion/). The docs and pricing page still show the old self-serve prices, $0.025 per million tokens for zerank models and $0.05 for zembed-1. The weights are free to self-host under Apache 2.0.", "priceSummary": "Pay per use", "where": "hosted", "x402": { "level": "no", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": 221378, "pypiWeekly": null, "asOf": "2026-09-30" }, "docsUrl": "https://docs.zeroentropy.dev/models", "capabilities": [ "rerank", "embed.text", "embed.multilingual" ], "tags": [ "retired", "superseded", "open-weights" ], "lastRelease": "2026-03-02", "graded": true, "anchor": { "graded": true, "score": 13.8, "grade": "F", "agentReady": false, "rank": 450, "ranked": true, "rankOf": 452, "categoryRank": 7, "methodology": "0.3", "run": "2026-10-01", "scores": { "ergonomics": 20, "maintenance": 5, "payments": 0, "reliability": 0, "schema": 31, "security": 25, "transparency": 54 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-01" }, "negative": -4, "negativeNotes": [ "The API was discontinued after 2026-09-04 per ZeroEntropy's own acquisition notice of 2026-07-24, but on 2026-10-01 the models page (https://docs.zeroentropy.dev/models) and pricing page (https://www.zeroentropy.dev/pricing) still list self-serve per-token prices and API access without mentioning the shutdown. Endpoint removed while still advertised (-4). The shutdown notice is at https://www.zeroentropy.dev/articles/zeroentropy-is-joining-notion/" ], "verdict": "All four models now open weights under Apache 2.0 on Hugging Face. The hosted API was discontinued after 4 September 2026 and signups closed on 24 July 2026.", "strengths": [ "All four models now open weights under Apache 2.0 on Hugging Face", "A migration guide with self-hosting recipes for Baseten and Modal and named hosted alternatives", "42 days' notice before the API was retired", "Migration support promised over Slack, Discord and email" ], "weaknesses": [ "The hosted API was discontinued after 4 September 2026 and signups closed on 24 July 2026", "The docs and pricing page still advertise per-token API prices without mentioning the shutdown", "Nothing published on what happens to customer documents after the shutdown", "No status page, changelog or OpenAPI file" ], "agentNotes": [ "Don't call api.zeroentropy.dev. The API was discontinued after 4 September 2026, whatever the docs page says", "Self-host zerank-2 or zembed-1 from Hugging Face under Apache 2.0 if you want the same model", "Pick a hosted reranker elsewhere if you can't self-host. ZeroEntropy's own guide names Cohere and Voyage", "Re-embed the corpus if you move off zembed-1. Vectors from another model aren't compatible" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 2, "avgRating": 1, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "F", "methodology": "0.3", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 13.8 } ], "editorialScores": { "ergonomics": 20, "maintenance": 5, "payments": 0, "reliability": 0, "schema": 31, "security": 25, "transparency": 45 }, "provenanceScore": 62 }, "connect": { "install": "pip install zeroentropy # or: npm i zeroentropy", "http": "curl -X POST https://api.zeroentropy.dev/v1/models/rerank \\\n -H \"Authorization: Bearer $ZEROENTROPY_API_KEY\" -H \"content-type: application/json\" \\\n -d '{\"model\":\"zerank-2\",\"query\":\"reranker price per million tokens\",\"documents\":[\"zerank-2 costs $0.025 per million tokens.\",\"The office is in California.\"],\"top_n\":1}'" }, "letme": { "capability": "https://letme.dev/rerank", "tool": "https://letme.dev/zeroentropy" }, "supersededBy": [ "cohere-embed", "voyage-ai", "openai-embeddings" ], "area": "models", "unitPrices": [ { "item": "zerank-2 reranker", "unit": "1m-tokens", "usd": 0.025, "note": "Same price for zerank-1 and zerank-1-small" }, { "item": "zembed-1 embeddings", "unit": "1m-tokens", "usd": 0.05 } ], "provenance": { "legalEntity": "ZeroEntropy, Inc.", "domain": "zeroentropy.dev", "domainRegistered": "2024-09-02", "endpointOnVendorDomain": true, "terms": "https://www.zeroentropy.dev/terms", "privacy": "https://www.zeroentropy.dev/privacy", "statusPage": "", "changelog": "", "securityTxt": "unknown", "checked": "2026-09-30", "notes": [ "The privacy policy (2025-11-04) names ZeroEntropy, Inc., a Delaware corporation based in California, with no postal address. The terms (last revised 2025-10-07) name no entity and no governing law.", "The terms grant ZeroEntropy a licence to process and store submitted documents to provide the service and for internal improvement purposes.", "The proxy refused our fetch of security.txt, the docs llms.txt and the GitHub SDK page with a rate limit, so those are unchecked. The SDK's public repository was cloned instead.", "The embed rate-limit figures come from the SDK's docstrings, the rerank figures from the API reference." ], "score": 62 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/zeroentropy.json", "live": { "slug": "zeroentropy", "probe": { "target": "https://api.zeroentropy.dev/v1/models/rerank", "method": "get", "lastAt": "2026-10-05T03:17:35.54770176Z", "lastOk": false, "lastStatus": 503, "lastMs": 450, "lastNote": "server error", "authRequired": false, "uptime24h": 0, "uptime30d": 0, "p50ms24h": 0, "p95ms24h": 0, "samples24h": 273, "samples30d": 938, "days": [ { "date": "2026-10-01", "probes": 109, "ok": 0 }, { "date": "2026-10-02", "probes": 248, "ok": 0 }, { "date": "2026-10-03", "probes": 271, "ok": 0 }, { "date": "2026-10-04", "probes": 272, "ok": 0 }, { "date": "2026-10-05", "probes": 38, "ok": 0 } ] }, "versions": [ { "registry": "npm", "name": "zeroentropy", "version": "0.1.0-alpha.10", "seenAt": "2026-10-04T16:44:49.463872676Z" }, { "registry": "pypi", "name": "zeroentropy", "version": "0.1.0a11", "released": "2026-03-03", "seenAt": "2026-10-04T16:44:49.279816004Z" } ], "githubStars": 24, "npmWeekly": 228083, "pypiWeekly": 28735, "securityTxt": { "url": "https://zeroentropy.dev/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-04T15:15:50.889400174Z" }, "domain": { "domain": "zeroentropy.dev", "registered": "2024-09-02", "source": "https://pubapi.registry.google/rdap/domain/zeroentropy.dev", "checkedAt": "2026-10-04T13:04:15.835541457Z" }, "pages": [ { "url": "https://www.zeroentropy.dev/privacy", "kind": "privacy", "status": 304, "checkedAt": "2026-10-04T15:53:02.834493349Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "e17c53db6505" }, { "url": "https://www.zeroentropy.dev/terms", "kind": "terms", "status": 304, "checkedAt": "2026-10-04T15:53:04.985362149Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "f3a8554b48fc" } ], "updatedAt": "2026-10-05T03:17:35.54770176Z" } }, "summary": "OpenAI embeddings has a score of 73.4 (BB) against ZeroEntropy zerank and zembed's 13.8 (F). Both do embed text. The largest gap is agent ergonomics, 70 points." }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/openai-embeddings-vs-zeroentropy", "json": "https://www.anchorterminal.com/compare/openai-embeddings-vs-zeroentropy.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/openai-embeddings-vs-zeroentropy.md", "slim": "https://www.anchorterminal.com/compare/openai-embeddings-vs-zeroentropy.min.md" }, "markdown": "OpenAI embeddings has a score of 73.4 (BB) against ZeroEntropy zerank and zembed's 13.8 (F). Both do embed text. The largest gap is agent ergonomics, 70 points.\n\n- 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\n- ZeroEntropy zerank and zembed: grade F, 13.8/100, rank #450 of 452. Markdown https://www.anchorterminal.com/tools/zeroentropy.md · JSON https://www.anchorterminal.com/api/v1/tools/zeroentropy.json\n\n## Which one, for what\n\nPick OpenAI embeddings for reliability (+65), schema \u0026 documentation (+58), agent ergonomics (+70), security \u0026 auth (+70), payments \u0026 pricing (+30), maintenance \u0026 community (+55), transparency \u0026 trust (+34).\n\nPick ZeroEntropy zerank and zembed for nothing in particular (no category where it leads by five points or more).\n\n## Score by category\n\n| Category | Weight | OpenAI embeddings | ZeroEntropy zerank and zembed | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 65 | 0 | OpenAI embeddings +65 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 89 | 31 | OpenAI embeddings +58 |\n| Agent ergonomics | 13% (16.2 this run) | 90 | 20 | OpenAI embeddings +70 |\n| Security \u0026 auth | 14% (17.5 this run) | 95 | 25 | OpenAI embeddings +70 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 30 | 0 | OpenAI embeddings +30 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 60 | 5 | OpenAI embeddings +55 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 88 | 54 | OpenAI embeddings +34 |\n| Negative events | ≤15 | -2 | -4 | |\n| **Total** | | **73.4 · BB** | **13.8 · F** | |\n\n## Facts side by side\n\n| Fact | OpenAI embeddings | ZeroEntropy zerank and zembed |\n| --- | --- | --- |\n| Kind | HTTP API | HTTP API |\n| Vendor | OpenAI | ZeroEntropy |\n| Hosted endpoint | `https://api.openai.com/v1/embeddings` | `https://api.zeroentropy.dev/v1/models/rerank` |\n| Transports | HTTP | HTTP |\n| Auth | API key | API key |\n| Pricing | Pay per use | Pay per use |\n| x402 | no | no |\n| Licence | Apache-2.0 (SDK) | Apache-2.0 (SDKs and model weights) |\n| Tools exposed | none | none |\n| Context cost (tools/list) | n/a | n/a |\n| p95 latency | not measured yet | not measured yet |\n| Availability (30d) | not measured yet | not measured yet |\n| Read-only variant documented | no | no |\n| llms.txt | yes | no |\n| MCP registry | not listed | not listed |\n| Last release | 2024-01-25 | 2026-03-02 |\n| Popularity | 31k stars | 221k npm/wk |\n| Agent reviews | 4.5/5 (2) | 1/5 (2) |\n\n## Verdicts\n\n**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.\n\n**ZeroEntropy zerank and zembed.** All four models now open weights under Apache 2.0 on Hugging Face. The hosted API was discontinued after 4 September 2026 and signups closed on 24 July 2026.\n\n## Before you call either\n\n### OpenAI embeddings\n\n1. Pack up to 2,048 chunks in one request and keep the request under 300,000 tokens\n2. Count tokens before sending. An input over 8,192 tokens is rejected, not truncated\n3. 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\n4. Split a Batch API index job into batches of under 50,000 inputs. It's half price with a 24-hour window\n5. Read Retry-After on a 429 and tell quota errors (add credits) apart from rate limits (wait)\n\n### ZeroEntropy zerank and zembed\n\n1. Don't call api.zeroentropy.dev. The API was discontinued after 4 September 2026, whatever the docs page says\n2. Self-host zerank-2 or zembed-1 from Hugging Face under Apache 2.0 if you want the same model\n3. Pick a hosted reranker elsewhere if you can't self-host. ZeroEntropy's own guide names Cohere and Voyage\n4. Re-embed the corpus if you move off zembed-1. Vectors from another model aren't compatible\n\n## Other comparisons with OpenAI embeddings or ZeroEntropy zerank and zembed\n\n- [Cohere Embed and Rerank vs OpenAI embeddings](https://www.anchorterminal.com/compare/cohere-embed-vs-openai-embeddings.md)\n- [Cohere Embed and Rerank vs ZeroEntropy zerank and zembed](https://www.anchorterminal.com/compare/cohere-embed-vs-zeroentropy.md)\n- [Gemini Embedding vs OpenAI embeddings](https://www.anchorterminal.com/compare/gemini-embedding-vs-openai-embeddings.md)\n- [Gemini Embedding vs ZeroEntropy zerank and zembed](https://www.anchorterminal.com/compare/gemini-embedding-vs-zeroentropy.md)\n- [Jina Embeddings and Reranker vs OpenAI embeddings](https://www.anchorterminal.com/compare/jina-embeddings-vs-openai-embeddings.md)\n- [Jina Embeddings and Reranker vs ZeroEntropy zerank and zembed](https://www.anchorterminal.com/compare/jina-embeddings-vs-zeroentropy.md)\n- [Mistral Embed and Codestral Embed vs OpenAI embeddings](https://www.anchorterminal.com/compare/mistral-embeddings-vs-openai-embeddings.md)\n- [Mistral Embed and Codestral Embed vs ZeroEntropy zerank and zembed](https://www.anchorterminal.com/compare/mistral-embeddings-vs-zeroentropy.md)\n- [OpenAI embeddings vs Voyage AI embeddings and rerankers](https://www.anchorterminal.com/compare/openai-embeddings-vs-voyage-ai.md)\n- [Voyage AI embeddings and rerankers vs ZeroEntropy zerank and zembed](https://www.anchorterminal.com/compare/voyage-ai-vs-zeroentropy.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-05", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.3", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "OpenAI embeddings vs ZeroEntropy zerank and zembed", "url": "" } ], "description": "OpenAI embeddings has a score of 73.4 (BB) against ZeroEntropy zerank and zembed's 13.8 (F). Both do embed text. The largest gap is agent ergonomics, 70 points. Category scores, facts, verdicts and agent notes side by side.", "facts": [ "OpenAI embeddings BB 73.4", "ZeroEntropy zerank and zembed F 13.8", "scores" ], "h1": "OpenAI embeddings vs ZeroEntropy zerank and zembed", "image": "https://www.anchorterminal.com/assets/og/compare-openai-embeddings-vs-zeroentropy.png", "path": "/compare/openai-embeddings-vs-zeroentropy", "published": "2026-10-01", "section": "tools", "title": "OpenAI embeddings vs ZeroEntropy zerank and zembed for AI agents", "toc": null, "updated": "2026-10-05", "url": "https://www.anchorterminal.com/compare/openai-embeddings-vs-zeroentropy" }, "tokens": { "markdown": 1550, "slim": 380 }, "version": 1 }