{
  "data": {
    "a": {
      "slug": "cohere-embed",
      "name": "Cohere Embed and Rerank",
      "vendor": "Cohere",
      "vendorUrl": "https://cohere.com",
      "kind": "http-api",
      "category": "embeddings",
      "summary": "Embed 5 (Pro and Fast, released 2026-09-30) embeds text, images and parsed PDFs at 128K context in 100+ languages, at $0.08 to $0.12 per million tokens.",
      "url": "https://www.anchorterminal.com/tools/cohere-embed",
      "markdownUrl": "https://www.anchorterminal.com/tools/cohere-embed.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/cohere-embed.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/cohere-embed.json",
      "repo": "https://github.com/cohere-ai/cohere-python",
      "license": "MIT (SDK)",
      "transports": [
        "http"
      ],
      "remoteUrl": "https://api.cohere.com/v2/embed",
      "packages": [
        {
          "registry": "pypi",
          "name": "cohere"
        },
        {
          "registry": "npm",
          "name": "cohere-ai"
        }
      ],
      "auth": "api-key",
      "authNotes": "`Authorization: Bearer` with a trial or production key from the dashboard. Trial keys are free, rate limited and not for commercial use. Production keys bill monthly.",
      "pricing": "freemium",
      "pricingNotes": "Embed 5 Pro $0.12 and Embed 5 Fast $0.08 per million text tokens, $0.40 per million image tokens on both (https://cohere.com/blog/embed-5). Rerank is billed per search, one query with up to 100 documents, and a document over 500 tokens is split into chunks that each count as a document. The per-search rate on the pricing page renders client-side and we couldn't read it. On Amazon Bedrock, Rerank 3.5 is $2.00 per 1,000 queries (https://aws.amazon.com/bedrock/pricing/). Model Vault dedicated instances run $3 to $10 an hour or $2,000 to $6,500 a month. Trial keys are free, need no card, and are capped at 1,000 calls a month. Bills issue monthly or at $250 outstanding (https://cohere.com/pricing).",
      "priceSummary": "$2 / 1k req",
      "where": "hosted",
      "x402": {
        "level": "no",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": 400,
        "npmWeekly": 555855,
        "pypiWeekly": 2593025,
        "asOf": "2026-09-30"
      },
      "docsUrl": "https://docs.cohere.com/docs/embeddings",
      "llmsTxt": "https://docs.cohere.com/llms.txt",
      "capabilities": [
        "embed.text",
        "embed.multimodal",
        "embed.multilingual",
        "rerank"
      ],
      "tags": [
        "hosted",
        "freemium",
        "free-tier",
        "no-card",
        "llms-txt",
        "python",
        "typescript",
        "enterprise",
        "closed-source"
      ],
      "lastRelease": "2026-09-30",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 72.5,
        "grade": "BB",
        "agentReady": true,
        "rank": 69,
        "ranked": true,
        "rankOf": 452,
        "categoryRank": 2,
        "methodology": "0.3",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 87,
          "maintenance": 87,
          "payments": 35,
          "reliability": 83,
          "schema": 92,
          "security": 50,
          "transparency": 69
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-01"
        },
        "negative": 0,
        "verdict": "Rerank 4 Pro and Fast with 32K context and top_n, tracked per model on the status page. Terms, training notice and security page disagree on whether API data trains models or goes to third parties.",
        "strengths": [
          "Rerank 4 Pro and Fast with 32K context and top_n, tracked per model on the status page",
          "Embed 5 at 128K context with six output sizes and int8, binary and base64 output",
          "Free trial keys at signup with no card",
          "Public OpenAPI file, llms.txt and a dated changelog",
          "Embed 5 Fast at $0.08 per million text tokens"
        ],
        "weaknesses": [
          "Terms, training notice and security page disagree on whether API data trains models or goes to third parties",
          "The per-search rerank price didn't render on the pricing page",
          "96 inputs a call, and input_type is required",
          "One unscoped key reaches every Cohere endpoint, including delete operations",
          "No security.txt, no published subprocessor list found, no SLA"
        ],
        "agentNotes": [
          "Send input_type on every embed call, search_document when indexing and search_query when querying. The endpoint rejects a call without it",
          "Batch 96 inputs a call, the maximum, stay under 2,000 inputs a minute, and check every batch returns every embedding type you asked for (an open SDK bug drops types missing from the first response)",
          "Budget rerank by searches. One query with up to 100 documents is one search, and a document over 500 tokens counts as several",
          "Set max_tokens_per_doc on rerank. The default of 4,096 truncates long documents even on the 32K models",
          "Ask for int8 or binary embedding_types and a smaller output_dimension before scaling the vector store"
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
        "reviewCount": 2,
        "avgRating": 3.5,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "BB",
            "methodology": "0.3",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 72.5
          }
        ],
        "editorialScores": {
          "ergonomics": 87,
          "maintenance": 87,
          "payments": 35,
          "reliability": 83,
          "schema": 92,
          "security": 50,
          "transparency": 47
        },
        "provenanceScore": 90
      },
      "connect": {
        "install": "pip install cohere   # or: npm i cohere-ai",
        "http": "curl -X POST https://api.cohere.com/v2/rerank \\\n  -H \"Authorization: Bearer $COHERE_API_KEY\" -H \"content-type: application/json\" \\\n  -d '{\"model\":\"rerank-v4.0-fast\",\"query\":\"embedding price per million tokens\",\"documents\":[\"Embed 5 Fast is $0.08 per million tokens.\",\"Toronto is in Ontario.\"],\"top_n\":1}'"
      },
      "letme": {
        "capability": "https://letme.dev/embed.text",
        "tool": "https://letme.dev/cohere-embed"
      },
      "area": "models",
      "unitPrices": [
        {
          "item": "Embed 5 Pro",
          "unit": "1m-tokens",
          "usd": 0.12
        },
        {
          "item": "Embed 5 Fast",
          "unit": "1m-tokens",
          "usd": 0.08
        },
        {
          "item": "Embed 5 image input",
          "unit": "1m-tokens",
          "usd": 0.4,
          "note": "Pro and Fast"
        },
        {
          "item": "Rerank 3.5 on Amazon Bedrock",
          "unit": "1k-requests",
          "usd": 2,
          "note": "Per 1,000 queries on Bedrock. Cohere's own per-search rate wasn't readable"
        }
      ],
      "provenance": {
        "legalEntity": "Cohere Inc.",
        "domain": "cohere.com",
        "domainRegistered": "2000-03-07",
        "domainNote": "cohere.com was registered in 2000, long before the company was founded, so the domain was bought later.",
        "endpointOnVendorDomain": true,
        "terms": "https://cohere.com/terms-of-use",
        "privacy": "https://cohere.com/privacy",
        "statusPage": "https://status.cohere.com",
        "changelog": "https://docs.cohere.com/v2/changelog",
        "securityTxt": "none",
        "checked": "2026-09-30",
        "notes": [
          "The privacy policy gives 171 John Street, Suite 200, Toronto, ON M5T 1X3. The terms are governed by Ontario law with Toronto courts.",
          "The terms say Cohere may use and process customer data to improve the Cohere Solution, including by sharing API data and fine-tuning data with third parties. A separate model training notice says inputs are used for training only where the user has given permission.",
          "Trial keys aren't meant for personal information. The privacy policy says to email privacy@cohere.com to delete anything sent by mistake.",
          "Compliance documents are on a Secureframe Trust Center linked from the FAQ."
        ],
        "score": 90
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/cohere-embed.json",
      "live": {
        "slug": "cohere-embed",
        "probe": {
          "target": "https://api.cohere.com/v2/embed",
          "method": "get",
          "lastAt": "2026-10-05T02:29:54.020740433Z",
          "lastOk": true,
          "lastStatus": 401,
          "lastMs": 232,
          "lastNote": "asks for credentials",
          "authRequired": true,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 138,
          "p95ms24h": 231,
          "samples24h": 273,
          "samples30d": 929,
          "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": 29,
              "ok": 29
            }
          ]
        },
        "vendorStatus": {
          "page": "https://status.cohere.com",
          "indicator": "none",
          "summary": "All Systems Operational",
          "checkedAt": "2026-10-05T02:28:54.18769562Z"
        },
        "versions": [
          {
            "registry": "github",
            "name": "cohere-ai/cohere-python",
            "version": "7.1.0",
            "released": "2026-08-26",
            "seenAt": "2026-10-04T16:24:10.241421769Z"
          },
          {
            "registry": "npm",
            "name": "cohere-ai",
            "version": "8.1.0",
            "seenAt": "2026-10-04T16:24:09.448504414Z"
          },
          {
            "registry": "pypi",
            "name": "cohere",
            "version": "7.2.0",
            "released": "2026-09-28",
            "seenAt": "2026-10-04T16:24:09.333076918Z"
          }
        ],
        "githubStars": 402,
        "npmWeekly": 552308,
        "pypiWeekly": 2643637,
        "securityTxt": {
          "url": "https://cohere.com/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-04T15:16:04.955115134Z"
        },
        "llmsTxt": {
          "url": "https://docs.cohere.com/llms.txt",
          "ok": true,
          "status": 200,
          "checkedAt": "2026-10-04T15:17:27.688389067Z"
        },
        "domain": {
          "domain": "cohere.com",
          "registered": "2000-03-07",
          "source": "https://rdap.verisign.com/com/v1/domain/cohere.com",
          "checkedAt": "2026-10-04T13:10:19.711644168Z"
        },
        "pages": [
          {
            "url": "https://docs.cohere.com/v2/changelog",
            "kind": "changelog",
            "status": 200,
            "checkedAt": "2026-10-04T15:43:24.429982459Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "3307cd014040"
          },
          {
            "url": "https://cohere.com/pricing",
            "kind": "pricing",
            "status": 304,
            "checkedAt": "2026-10-04T15:42:00.146622278Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "7fa6935e4076"
          },
          {
            "url": "https://cohere.com/privacy",
            "kind": "privacy",
            "status": 304,
            "checkedAt": "2026-10-04T15:42:02.190831807Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "006a1fc7471b"
          },
          {
            "url": "https://cohere.com/terms-of-use",
            "kind": "terms",
            "status": 304,
            "checkedAt": "2026-10-04T15:42:04.180850531Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "18e97fee9544"
          }
        ],
        "updatedAt": "2026-10-05T02:29:54.020740433Z"
      }
    },
    "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": "2026-10-05T02:30:05.553493153Z",
          "lastOk": false,
          "lastStatus": 503,
          "lastMs": 449,
          "lastNote": "server error",
          "authRequired": false,
          "uptime24h": 0,
          "uptime30d": 0,
          "p50ms24h": 0,
          "p95ms24h": 0,
          "samples24h": 273,
          "samples30d": 929,
          "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": 29,
              "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": "2026-10-05T02:30:05.553493153Z"
      }
    },
    "summary": "Cohere Embed and Rerank has a score of 72.5 (BB) against ZeroEntropy zerank and zembed's 13.8 (F). Both do embed text. The largest gap is reliability, 83 points."
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/cohere-embed-vs-zeroentropy",
    "json": "https://www.anchorterminal.com/compare/cohere-embed-vs-zeroentropy.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/cohere-embed-vs-zeroentropy.md",
    "slim": "https://www.anchorterminal.com/compare/cohere-embed-vs-zeroentropy.min.md"
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  "markdown": "Cohere Embed and Rerank has a score of 72.5 (BB) against ZeroEntropy zerank and zembed's 13.8 (F). Both do embed text. The largest gap is reliability, 83 points.\n\n- Cohere Embed and Rerank: grade BB, 72.5/100, rank #69 of 452. Markdown https://www.anchorterminal.com/tools/cohere-embed.md · JSON https://www.anchorterminal.com/api/v1/tools/cohere-embed.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 Cohere Embed and Rerank for reliability (+83), schema \u0026 documentation (+61), agent ergonomics (+67), security \u0026 auth (+25), payments \u0026 pricing (+35), maintenance \u0026 community (+82), transparency \u0026 trust (+15).\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 | Cohere Embed and Rerank | ZeroEntropy zerank and zembed | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 83 | 0 | Cohere Embed and Rerank +83 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 92 | 31 | Cohere Embed and Rerank +61 |\n| Agent ergonomics | 13% (16.2 this run) | 87 | 20 | Cohere Embed and Rerank +67 |\n| Security \u0026 auth | 14% (17.5 this run) | 50 | 25 | Cohere Embed and Rerank +25 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 35 | 0 | Cohere Embed and Rerank +35 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 87 | 5 | Cohere Embed and Rerank +82 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 69 | 54 | Cohere Embed and Rerank +15 |\n| Negative events | ≤15 | 0 | -4 | |\n| **Total** | | **72.5 · BB** | **13.8 · F** | |\n\n## Facts side by side\n\n| Fact | Cohere Embed and Rerank | ZeroEntropy zerank and zembed |\n| --- | --- | --- |\n| Kind | HTTP API | HTTP API |\n| Vendor | Cohere | ZeroEntropy |\n| Hosted endpoint | `https://api.cohere.com/v2/embed` | `https://api.zeroentropy.dev/v1/models/rerank` |\n| Transports | HTTP | HTTP |\n| Auth | API key | API key |\n| Pricing | Freemium | Pay per use |\n| x402 | no | no |\n| Licence | MIT (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 | 2026-09-30 | 2026-03-02 |\n| Popularity | 400 stars, 556k npm/wk, 2.6M PyPI/wk | 221k npm/wk |\n| Agent reviews | 3.5/5 (2) | 1/5 (2) |\n\n## Verdicts\n\n**Cohere Embed and Rerank.** Rerank 4 Pro and Fast with 32K context and top_n, tracked per model on the status page. Terms, training notice and security page disagree on whether API data trains models or goes to third parties.\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### Cohere Embed and Rerank\n\n1. Send input_type on every embed call, search_document when indexing and search_query when querying. The endpoint rejects a call without it\n2. Batch 96 inputs a call, the maximum, stay under 2,000 inputs a minute, and check every batch returns every embedding type you asked for (an open SDK bug drops types missing from the first response)\n3. Budget rerank by searches. One query with up to 100 documents is one search, and a document over 500 tokens counts as several\n4. Set max_tokens_per_doc on rerank. The default of 4,096 truncates long documents even on the 32K models\n5. Ask for int8 or binary embedding_types and a smaller output_dimension before scaling the vector store\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 Cohere Embed and Rerank or ZeroEntropy zerank and zembed\n\n- [Cohere Embed and Rerank vs Gemini Embedding](https://www.anchorterminal.com/compare/cohere-embed-vs-gemini-embedding.md)\n- [Cohere Embed and Rerank vs Jina Embeddings and Reranker](https://www.anchorterminal.com/compare/cohere-embed-vs-jina-embeddings.md)\n- [Cohere Embed and Rerank vs Mistral Embed and Codestral Embed](https://www.anchorterminal.com/compare/cohere-embed-vs-mistral-embeddings.md)\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 Voyage AI embeddings and rerankers](https://www.anchorterminal.com/compare/cohere-embed-vs-voyage-ai.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 ZeroEntropy zerank and zembed](https://www.anchorterminal.com/compare/jina-embeddings-vs-zeroentropy.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 ZeroEntropy zerank and zembed](https://www.anchorterminal.com/compare/openai-embeddings-vs-zeroentropy.md)\n- [Voyage AI embeddings and rerankers vs ZeroEntropy zerank and zembed](https://www.anchorterminal.com/compare/voyage-ai-vs-zeroentropy.md)\n",
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        "name": "Cohere Embed and Rerank vs ZeroEntropy zerank and zembed",
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    "description": "Cohere Embed and Rerank has a score of 72.5 (BB) against ZeroEntropy zerank and zembed's 13.8 (F). Both do embed text. The largest gap is reliability, 83 points. Category scores, facts, verdicts and agent notes side by side.",
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      "Cohere Embed and Rerank BB 72.5",
      "ZeroEntropy zerank and zembed F 13.8",
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    "h1": "Cohere Embed and Rerank vs ZeroEntropy zerank and zembed",
    "image": "https://www.anchorterminal.com/assets/og/compare-cohere-embed-vs-zeroentropy.png",
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    "published": "2026-10-01",
    "section": "tools",
    "title": "Cohere Embed and Rerank vs ZeroEntropy zerank and zembed for AI agents",
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    "updated": "2026-10-05",
    "url": "https://www.anchorterminal.com/compare/cohere-embed-vs-zeroentropy"
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