{ "data": { "a": { "slug": "amazon-nova-embeddings", "name": "Amazon Nova Multimodal Embeddings", "vendor": "Amazon Web Services", "vendorUrl": "https://aws.amazon.com/nova/", "kind": "http-api", "category": "embeddings", "summary": "Amazon Nova Multimodal Embeddings is an AWS model on Amazon Bedrock that turns text, images, document images, video and audio into vectors in one space, at 256, 384, 1024 or 3072 dimensions, through synchronous and asynchronous calls.", "url": "https://www.anchorterminal.com/tools/amazon-nova-embeddings", "markdownUrl": "https://www.anchorterminal.com/tools/amazon-nova-embeddings.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/amazon-nova-embeddings.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/amazon-nova-embeddings.json", "license": "Proprietary service under the AWS Service Terms. The AWS SDKs are Apache-2.0", "transports": [ "http" ], "remoteUrl": "https://bedrock-runtime.us-east-1.amazonaws.com", "packages": [ { "registry": "pypi", "name": "boto3" }, { "registry": "npm", "name": "@aws-sdk/client-bedrock-runtime" } ], "auth": "api-key", "authNotes": "AWS Signature Version 4 with IAM credentials or a role, or an Amazon Bedrock API key sent as a bearer token (`AWS_BEARER_TOKEN_BEDROCK`). Short-term keys last up to 12 hours and inherit the caller's IAM permissions. Long-term keys create an IAM user and AWS recommends them for exploration only. Access is self-serve once a person has an AWS account, and asynchronous calls also need write access to an S3 bucket (https://docs.aws.amazon.com/bedrock/latest/userguide/api-keys.html).", "pricing": "usage", "pricingNotes": "On demand in US East (N. Virginia), text input is $0.135 per million tokens, a standard image $0.00006, a document image $0.0006, video $0.0007 a second and audio $0.00014 a second. Batch is $0.0675 per million text tokens, with lower media rates. GovCloud prices are 20 per cent higher. There is no model-specific free tier. New AWS accounts can receive up to $200 in Free Tier credits, which lets an agent's owner start without a contract (https://aws.amazon.com/bedrock/pricing/).", "priceSummary": "Pay per use", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the Nova guide, the Bedrock model card or the pricing page (checked 2026-10-08).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": 18066100, "pypiWeekly": 573748207, "asOf": "2026-10-08" }, "docsUrl": "https://docs.aws.amazon.com/nova/latest/userguide/nova-embeddings.html", "llmsTxt": "https://docs.aws.amazon.com/nova/latest/userguide/llms.txt", "capabilities": [ "embed.text", "embed.multimodal" ], "tags": [ "official", "hosted", "usage-priced", "closed-source", "python", "typescript", "llms-txt", "batch", "async-jobs", "enterprise" ], "lastRelease": "2025-10-28", "graded": true, "anchor": { "graded": true, "score": 75, "grade": "BB", "agentReady": true, "rank": 59, "ranked": true, "rankOf": 842, "categoryRank": 1, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 78, "maintenance": 50, "payments": 30, "reliability": 95, "schema": 76, "security": 91, "transparency": 79 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-08" }, "negative": 0, "verdict": "One model embeds text, images, document images, video and audio into a shared space, with nine documented purpose settings and published per-unit prices. It runs in US East (N. Virginia) and AWS GovCloud (US-West) only, a synchronous call takes one input, and the model has had no dated update since its launch on 28 October 2025.", "bestFor": "Suited to mixed-media retrieval for teams already on AWS, especially video and audio archives processed through S3.", "strengths": [ "Text, images, document images, video and audio share one vector space, with four output sizes from 256 to 3072", "`embeddingPurpose` has nine documented values, with separate settings for indexing and for each retrieval type", "Published quotas of 2,000 requests a minute and 30 concurrent asynchronous jobs per Region", "Bedrock stores no model inputs or outputs by default, and this model is not on the abuse-detection retention list", "The asynchronous API segments long text, audio and video itself and writes one embedding per segment to S3" ], "weaknesses": [ "In-Region inference in us-east-1 and us-gov-west-1 only, with no cross-Region inference profile", "A synchronous request embeds one item, with at most 8,192 characters of inline text or 30 seconds of audio or video", "The Bedrock model card marks Invoke as unsupported while the Nova guide documents `InvokeModel` for synchronous calls", "No dated change to the model was found after its launch on 28 October 2025", "Both quotas are marked not adjustable through Service Quotas" ], "agentNotes": [ "Call `bedrock-runtime` in us-east-1 with model ID `amazon.nova-2-multimodal-embeddings-v1:0`. No other commercial Region serves it", "Index with `embeddingPurpose` `GENERIC_INDEX`, then embed queries with the retrieval value that matches the index, such as `TEXT_RETRIEVAL` or `GENERIC_RETRIEVAL`", "Always send `truncationMode` with text. It is required, and `NONE` fails the request when the text is too long", "Use `StartAsyncInvoke` with an S3 output bucket for anything over 30 seconds or 8,192 characters, and pass `clientRequestToken` so a retry doesn't start a second job", "Keep one `embeddingDimension` per index. The default is 3072" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "BB", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 75 } ], "editorialScores": { "ergonomics": 78, "maintenance": 50, "payments": 30, "reliability": 95, "schema": 76, "security": 91, "transparency": 69 }, "provenanceScore": 88 }, "connect": { "install": "pip install boto3" }, "letme": { "capability": "https://letme.dev/embed.text", "tool": "https://letme.dev/amazon-nova-embeddings" }, "sameCompany": [ "amazon-bedrock-guardrails", "amazon-transcribe", "amazon-polly", "agentcore-memory", "agentcore-identity", "aws-secrets-manager", "aws-mcp-servers", "amazon-ses", "amazon-location", "amazon-translate", "amazon-ads-api" ], "area": "models", "unitPrices": [ { "item": "Text input, on demand", "unit": "1m-tokens", "usd": 0.135, "note": "US East (N. Virginia)" }, { "item": "Text input, batch", "unit": "1m-tokens", "usd": 0.0675 }, { "item": "Standard image input", "unit": "image", "usd": 0.00006, "note": "Batch $0.00003" }, { "item": "Document image input", "unit": "image", "usd": 0.0006, "note": "Batch $0.00048" }, { "item": "Video input", "unit": "video-second", "usd": 0.0007, "note": "Batch $0.00056" }, { "item": "Audio input", "unit": "audio-minute", "usd": 0.0084, "note": "$0.00014 a second. Batch $0.000112 a second" } ], "provenance": { "legalEntity": "Amazon Web Services, Inc.", "domain": "amazon.com", "domainRegistered": "1994-11-01", "domainNote": "The endpoint is on amazonaws.com, an AWS domain registered on 2005-08-18. The security.txt on aws.amazon.com passed its Expires date on 2026-09-24.", "endpointOnVendorDomain": true, "terms": "https://aws.amazon.com/service-terms/", "privacy": "https://aws.amazon.com/privacy/", "statusPage": "https://health.aws.amazon.com/health/status", "changelog": "https://docs.aws.amazon.com/bedrock/latest/userguide/doc-history.html", "securityTxt": "expired", "checked": "2026-10-08", "notes": [ "The AWS Service Terms were last updated on 1 October 2026. Section 50.12 covers Amazon Bedrock, and Bedrock is not among the services section 50.3 lists for use of content to improve AWS services.", "RDAP gives 1994-11-01 for amazon.com and 2005-08-18 for amazonaws.com.", "aws.amazon.com/.well-known/security.txt has Contact and Policy fields. Its Expires value is 2026-09-24T16:25:03Z, which had passed on 2026-10-08.", "The pricing page draws its tables by script. Prices were read from the price feed the page loads, for US East (N. Virginia).", "The legal entity is as the existing AWS listings record it. The AWS Customer Agreement and the privacy notice were not re-read in this run." ], "score": 88 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/amazon-nova-embeddings.json", "live": { "slug": "amazon-nova-embeddings", "probe": { "target": "https://bedrock-runtime.us-east-1.amazonaws.com", "method": "get", "lastAt": "2026-10-09T10:42:35.138522771Z", "lastOk": true, "lastStatus": 404, "lastMs": 261, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 258, "p95ms24h": 279, "samples24h": 33, "samples30d": 33, "days": [ { "date": "2026-10-09", "probes": 33, "ok": 33 } ] }, "updatedAt": "2026-10-09T10:42:35.138522771Z" } }, "answer": "Amazon Nova Multimodal Embeddings scores 75 (BB) on agent readiness against Jina Embeddings and Reranker's 61 (C), and leads in 3 of 7 scored categories. Jina Embeddings and Reranker leads on schema \u0026 documentation, agent ergonomics and maintenance \u0026 community.", "b": { "slug": "jina-embeddings", "name": "Jina Embeddings and Reranker", "vendor": "Jina AI (Elastic)", "vendorUrl": "https://jina.ai", "kind": "http-api", "category": "embeddings", "summary": "jina-embeddings-v5 in text and omni (text, image, audio, video, PDF) variants at up to 32,768 tokens, plus the jina-reranker-v3.5 at 131,072 tokens a call.", "url": "https://www.anchorterminal.com/tools/jina-embeddings", "markdownUrl": "https://www.anchorterminal.com/tools/jina-embeddings.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/jina-embeddings.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/jina-embeddings.json", "repo": "https://github.com/jina-ai/MCP", "license": "Apache-2.0 (MCP server)", "transports": [ "http", "streamable-http" ], "remoteUrl": "https://api.jina.ai/v1/embeddings", "packages": [], "auth": "api-key", "authNotes": "`Authorization: Bearer` with a `jina_...` key. A new account gets a key with free tokens, and the same key works for Reader, Search, Embeddings, Reranker and the MCP server.", "pricing": "freemium", "pricingNotes": "Prepaid tokens, topped up through Stripe (cards, Google Pay, PayPal) and shared across every Jina API. A new key comes with free tokens. Non-text inputs are converted to tokens by the encoder, about 363 tokens an image on v5-omni, 4,840 on v4 and 16,000 on jina-clip-v2. Jina changed its pricing model on 2025-05-06, and the public pages don't state a US dollar price per token, so we don't list one (https://jina.ai/embeddings/).", "priceSummary": "Freemium", "where": "hosted", "x402": { "level": "no", "endpoints": [] }, "toolCount": 12, "popularity": { "githubStars": 841, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-09-30" }, "docsUrl": "https://jina.ai/embeddings/", "llmsTxt": "https://jina.ai/models/llms.txt", "openapi": "https://api.jina.ai/openapi.json", "capabilities": [ "embed.text", "embed.multimodal", "embed.code", "embed.multilingual", "rerank" ], "tags": [ "hosted", "freemium", "free-tier", "no-card", "mcp", "prepaid", "eu" ], "lastRelease": "2026-09-18", "graded": true, "anchor": { "graded": true, "score": 61, "grade": "C", "agentReady": false, "rank": 438, "ranked": true, "rankOf": 842, "categoryRank": 5, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 86, "maintenance": 62, "payments": 30, "reliability": 65, "schema": 84, "security": 35, "transparency": 58 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-01" }, "negative": 0, "verdict": "jina-reranker-v3.5 (20 July 2026) with a 131,072-token window and no document cap. No price per token in any currency on the public pages.", "bestFor": "Reranking large candidate sets and multimodal corpora with audio or video.", "strengths": [ "jina-reranker-v3.5 (20 July 2026) with a 131,072-token window and no document cap", "v5-omni embeds text, images, audio, video and PDFs into one space", "OpenAPI 3.1 file with enums for model, task and embedding_type, and error responses from 400 to 504", "Hosted MCP server with rerank and dedupe tools, filterable per client", "Doesn't train on inputs, per the terms" ], "weaknesses": [ "No price per token in any currency on the public pages", "One prepaid balance shared with Reader and Search, so a scraping job can drain the embedding budget", "26 automated incidents on the status feed from 15 September to 1 October 2026, and no status component for v5-omni or reranker v3.5", "No security.txt, no SLA and no API changelog", "The MCP server has no CI or tests, and current weights are CC BY-NC 4.0" ], "agentNotes": [ "Send the whole candidate set to rerank in one call. The 131K window on v3.5 fits hundreds of chunks", "On a 429, back off exponentially. Limits count per key when a key is sent, per IP otherwise", "Use /v1/batch/embeddings for large corpora rather than a loop of synchronous calls", "Add include_tags=rerank on the MCP URL to load only sort_by_relevance and deduplicate_strings", "Count image tokens before a big multimodal job, about 363 an image on v5-omni" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 2, "avgRating": 3, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 61 } ], "editorialScores": { "ergonomics": 86, "maintenance": 62, "payments": 30, "reliability": 65, "schema": 84, "security": 35, "transparency": 45 }, "provenanceScore": 70 }, "connect": { "http": "curl https://api.jina.ai/v1/rerank \\\n -H \"Authorization: Bearer $JINA_API_KEY\" -H \"content-type: application/json\" \\\n -d '{\"model\":\"jina-reranker-v3.5\",\"query\":\"embedding price per million tokens\",\"documents\":[\"Tokens are prepaid and shared across APIs.\",\"Berlin is in Germany.\"],\"top_n\":1}'", "claudeCode": "claude mcp add --transport http jina \"https://mcp.jina.ai/v1?include_tags=rerank\" --header \"Authorization: Bearer $JINA_API_KEY\"", "config": { "mcpServers": { "jina": { "headers": { "Authorization": "Bearer ${JINA_API_KEY}" }, "url": "https://mcp.jina.ai/v1?include_tags=rerank" } } } }, "letme": { "capability": "https://letme.dev/embed.text", "tool": "https://letme.dev/jina-embeddings" }, "sameCompany": [ "jina-reader" ], "area": "models", "provenance": { "legalEntity": "Jina AI GmbH", "domain": "jina.ai", "domainRegistered": "2020-01-20", "domainNote": "Jina AI GmbH is a subsidiary of Elastic N.V. since October 2025, and the privacy statement is Elastic's.", "endpointOnVendorDomain": true, "terms": "https://jina.ai/legal/", "privacy": "https://www.elastic.co/legal/privacy-statement", "statusPage": "https://status.jina.ai", "changelog": "", "securityTxt": "none", "checked": "2026-10-02", "notes": [ "The terms give Prinzessinnenstraße 19-20, 10969 Berlin, Germany, under German law with Berlin courts.", "jina.ai/.well-known/security.txt returns 404. The root jina.ai/llms.txt returns 404, but the embeddings page links llms.txt at jina.ai/models/llms.txt, an OpenAPI 3.1 document at api.jina.ai/openapi.json and API docs at api.jina.ai/scalar.", "The MCP server's source is public under Apache-2.0 (version 1.10.0, last commit 2026-09-18)." ], "score": 70 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/jina-embeddings.json", "live": { "slug": "jina-embeddings", "probe": { "target": "https://api.jina.ai/v1/embeddings", "method": "get", "lastAt": "2026-10-09T10:42:46.188660172Z", "lastOk": true, "lastStatus": 401, "lastMs": 186, "lastNote": "asks for credentials", "authRequired": true, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 192, "p95ms24h": 266, "samples24h": 260, "samples30d": 2098, "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": 272, "ok": 272 }, { "date": "2026-10-06", "probes": 272, "ok": 272 }, { "date": "2026-10-07", "probes": 272, "ok": 272 }, { "date": "2026-10-08", "probes": 268, "ok": 268 }, { "date": "2026-10-09", "probes": 114, "ok": 114 } ] }, "vendorStatus": { "page": "https://status.jina.ai", "indicator": "none", "summary": "All Systems Operational", "checkedAt": "2026-10-09T10:41:45.539354849Z" }, "githubStars": 875, "securityTxt": { "url": "https://jina.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-08T15:38:49.272613996Z" }, "llmsTxt": { "url": "https://jina.ai/models/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-10-08T14:00:33.128296706Z" }, "domain": { "domain": "jina.ai", "registered": "2020-01-20", "source": "https://rdap.identitydigital.services/rdap/domain/jina.ai", "checkedAt": "2026-10-04T13:08:08.912440143Z" }, "pages": [ { "url": "https://www.elastic.co/legal/privacy-statement", "kind": "privacy", "status": 200, "checkedAt": "2026-10-08T18:27:33.853078847Z", "changedAt": "2026-10-07T18:11:44.162717631Z", "fingerprint": "33a9d69f6773" }, { "url": "https://jina.ai/legal/", "kind": "terms", "status": 200, "checkedAt": "2026-10-08T18:21:02.830277731Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "822c862ff72d" } ], "updatedAt": "2026-10-09T10:42:46.188660172Z" } }, "facts": [ { "a": "HTTP API", "b": "HTTP API", "name": "Kind" }, { "a": "Amazon Web Services", "b": "Jina AI (Elastic)", "name": "Vendor" }, { "a": "https://bedrock-runtime.us-east-1.amazonaws.com", "b": "https://api.jina.ai/v1/embeddings", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP, Streamable HTTP", "name": "Transports" }, { "a": "API key", "b": "API key", "name": "Auth" }, { "a": "Pay per use", "b": "Freemium", "name": "Pricing" }, { "a": "$0.0675 per 1M tokens", "b": "not published", "name": "Price for embed text" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Proprietary service under the AWS Service Terms. The AWS SDKs are Apache-2.0", "b": "Apache-2.0 (MCP server)", "name": "Licence" }, { "a": "none", "b": "12", "name": "Tools exposed" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2025-10-28", "b": "2026-09-18", "name": "Last release" }, { "a": "2026-10-01", "b": "2026-05-04", "name": "Terms last updated" }, { "a": "2026-05-18", "b": "2026-09-07", "name": "Privacy policy last updated" }, { "a": "yes, with an opt-out", "b": "not found in the text", "name": "Customer content may train models" }, { "a": "yes", "b": "yes", "name": "Terms restrict automated access" }, { "a": "yes", "b": "yes", "name": "Terms restrict benchmarking" }, { "a": "yes", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "not found in the text", "name": "Arbitration or class-action waiver" }, { "a": "18.1M npm/wk, 573.7M PyPI/wk", "b": "841 stars", "name": "Popularity" }, { "a": "none", "b": "3/5 (2)", "name": "Agent reviews" } ], "faq": [ { "answer": "Amazon Nova Multimodal Embeddings scores 75 (BB) on agent readiness against Jina Embeddings and Reranker's 61 (C), and leads in 3 of 7 scored categories. Jina Embeddings and Reranker leads on schema \u0026 documentation, agent ergonomics and maintenance \u0026 community.", "question": "Which is better for AI agents, Amazon Nova Multimodal Embeddings or Jina Embeddings and Reranker?" }, { "answer": "Both need an API key.", "question": "Do Amazon Nova Multimodal Embeddings and Jina Embeddings and Reranker need an API key?" }, { "answer": "Yes. Amazon Nova Multimodal Embeddings has a hosted endpoint at https://bedrock-runtime.us-east-1.amazonaws.com and Jina Embeddings and Reranker at https://api.jina.ai/v1/embeddings.", "question": "Can an agent call Amazon Nova Multimodal Embeddings and Jina Embeddings and Reranker without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 95 against 65", "Security \u0026 auth, 91 against 35", "Transparency \u0026 trust, 79 against 58" ], "also": [ "Agent-ready, a grade of BB or better" ], "goodFor": "Suited to mixed-media retrieval for teams already on AWS, especially video and audio archives processed through S3.", "slug": "amazon-nova-embeddings", "watchFor": "In-Region inference in us-east-1 and us-gov-west-1 only, with no cross-Region inference profile" }, { "aheadOn": [ "Schema \u0026 documentation, 84 against 76", "Agent ergonomics, 86 against 78", "Maintenance \u0026 community, 62 against 50" ], "also": [ "Free to start without a card" ], "goodFor": "Reranking large candidate sets and multimodal corpora with audio or video.", "slug": "jina-embeddings", "watchFor": "No price per token in any currency on the public pages" } ], "job": { "capability": "embed.text", "name": "Embed text" }, "others": [ { "json": "https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-cohere-embed.json", "title": "Amazon Nova Multimodal Embeddings vs Cohere Embed and Rerank", "url": "https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-cohere-embed" }, { "json": "https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-gemini-embedding.json", "title": "Amazon Nova Multimodal Embeddings vs Gemini Embedding", "url": "https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-gemini-embedding" }, { "json": "https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-mistral-embeddings.json", "title": "Amazon Nova Multimodal Embeddings vs Mistral Embed and Codestral Embed", "url": "https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-mistral-embeddings" }, { "json": "https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-nomic-embed.json", "title": "Amazon Nova Multimodal Embeddings vs Nomic Embed", "url": "https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-nomic-embed" }, { "json": "https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-nvidia-nemo-retriever.json", "title": "Amazon Nova Multimodal Embeddings vs NVIDIA NeMo Retriever Embedding and Reranking NIMs", "url": "https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-nvidia-nemo-retriever" }, { "json": "https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-openai-embeddings.json", "title": "Amazon Nova Multimodal Embeddings vs OpenAI embeddings", "url": "https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-openai-embeddings" }, { "json": "https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-voyage-ai.json", "title": "Amazon Nova Multimodal Embeddings vs Voyage AI embeddings and rerankers", "url": "https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-voyage-ai" }, { "json": "https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-zeroentropy.json", "title": "Amazon Nova Multimodal Embeddings vs ZeroEntropy zerank and zembed", "url": "https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-zeroentropy" }, { "json": "https://www.anchorterminal.com/compare/cohere-embed-vs-jina-embeddings.json", "title": "Cohere Embed and Rerank vs Jina Embeddings and Reranker", "url": "https://www.anchorterminal.com/compare/cohere-embed-vs-jina-embeddings" }, { "json": "https://www.anchorterminal.com/compare/gemini-embedding-vs-jina-embeddings.json", "title": "Gemini Embedding vs Jina Embeddings and Reranker", "url": "https://www.anchorterminal.com/compare/gemini-embedding-vs-jina-embeddings" }, { "json": "https://www.anchorterminal.com/compare/jina-embeddings-vs-mistral-embeddings.json", "title": "Jina Embeddings and Reranker vs Mistral Embed and Codestral Embed", "url": "https://www.anchorterminal.com/compare/jina-embeddings-vs-mistral-embeddings" }, { "json": "https://www.anchorterminal.com/compare/jina-embeddings-vs-nomic-embed.json", "title": "Jina Embeddings and Reranker vs Nomic Embed", "url": "https://www.anchorterminal.com/compare/jina-embeddings-vs-nomic-embed" }, { "json": "https://www.anchorterminal.com/compare/jina-embeddings-vs-nvidia-nemo-retriever.json", "title": "Jina Embeddings and Reranker vs NVIDIA NeMo Retriever Embedding and Reranking NIMs", "url": "https://www.anchorterminal.com/compare/jina-embeddings-vs-nvidia-nemo-retriever" }, { "json": "https://www.anchorterminal.com/compare/jina-embeddings-vs-openai-embeddings.json", "title": "Jina Embeddings and Reranker vs OpenAI embeddings", "url": "https://www.anchorterminal.com/compare/jina-embeddings-vs-openai-embeddings" }, { "json": "https://www.anchorterminal.com/compare/jina-embeddings-vs-voyage-ai.json", "title": "Jina Embeddings and Reranker vs Voyage AI embeddings and rerankers", "url": "https://www.anchorterminal.com/compare/jina-embeddings-vs-voyage-ai" }, { "json": "https://www.anchorterminal.com/compare/jina-embeddings-vs-zeroentropy.json", "title": "Jina Embeddings and Reranker vs ZeroEntropy zerank and zembed", "url": "https://www.anchorterminal.com/compare/jina-embeddings-vs-zeroentropy" } ], "scores": [ { "amazon-nova-embeddings": 95, "by": 30, "edge": "amazon-nova-embeddings", "jina-embeddings": 65, "key": "reliability", "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "amazon-nova-embeddings": 76, "by": 8, "edge": "jina-embeddings", "jina-embeddings": 84, "key": "schema", "name": "Schema \u0026 documentation", "weight": 13 }, { "amazon-nova-embeddings": 78, "by": 8, "edge": "jina-embeddings", "jina-embeddings": 86, "key": "ergonomics", "name": "Agent ergonomics", "weight": 13 }, { "amazon-nova-embeddings": 91, "by": 56, "edge": "amazon-nova-embeddings", "jina-embeddings": 35, "key": "security", "name": "Security \u0026 auth", "weight": 14 }, { "amazon-nova-embeddings": 30, "by": 0, "edge": "", "jina-embeddings": 30, "key": "payments", "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "amazon-nova-embeddings": 50, "by": 12, "edge": "jina-embeddings", "jina-embeddings": 62, "key": "maintenance", "name": "Maintenance \u0026 community", "weight": 7 }, { "amazon-nova-embeddings": 79, "by": 21, "edge": "amazon-nova-embeddings", "jina-embeddings": 58, "key": "transparency", "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Amazon Nova Multimodal Embeddings scores 75 (BB) on agent readiness against Jina Embeddings and Reranker's 61 (C), and leads in 3 of 7 scored categories. Jina Embeddings and Reranker leads on schema \u0026 documentation, agent ergonomics and maintenance \u0026 community. Both do embed text.", "verdicts": { "amazon-nova-embeddings": "One model embeds text, images, document images, video and audio into a shared space, with nine documented purpose settings and published per-unit prices. It runs in US East (N. Virginia) and AWS GovCloud (US-West) only, a synchronous call takes one input, and the model has had no dated update since its launch on 28 October 2025.", "jina-embeddings": "jina-reranker-v3.5 (20 July 2026) with a 131,072-token window and no document cap. No price per token in any currency on the public pages." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-jina-embeddings", "json": "https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-jina-embeddings.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-jina-embeddings.md", "slim": "https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-jina-embeddings.min.md" }, "markdown": "Amazon Nova Multimodal Embeddings scores 75 (BB) on agent readiness against Jina Embeddings and Reranker's 61 (C), and leads in 3 of 7 scored categories. Jina Embeddings and Reranker leads on schema \u0026 documentation, agent ergonomics and maintenance \u0026 community. Both do embed text.\n\n- Amazon Nova Multimodal Embeddings: grade BB, 75/100, rank #59 of 842. Markdown https://www.anchorterminal.com/tools/amazon-nova-embeddings.md · JSON https://www.anchorterminal.com/api/v1/tools/amazon-nova-embeddings.json\n- Jina Embeddings and Reranker: grade C, 61/100, rank #438 of 842. Markdown https://www.anchorterminal.com/tools/jina-embeddings.md · JSON https://www.anchorterminal.com/api/v1/tools/jina-embeddings.json\n\n## Which one, for what\n\n### Amazon Nova Multimodal Embeddings (BB)\n\nGood for: Suited to mixed-media retrieval for teams already on AWS, especially video and audio archives processed through S3.\n\nAhead on:\n- Reliability, 95 against 65\n- Security \u0026 auth, 91 against 35\n- Transparency \u0026 trust, 79 against 58\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n\nWatch for: In-Region inference in us-east-1 and us-gov-west-1 only, with no cross-Region inference profile\n\n### Jina Embeddings and Reranker (C)\n\nGood for: Reranking large candidate sets and multimodal corpora with audio or video.\n\nAhead on:\n- Schema \u0026 documentation, 84 against 76\n- Agent ergonomics, 86 against 78\n- Maintenance \u0026 community, 62 against 50\n\nAlso in its favour:\n- Free to start without a card\n\nWatch for: No price per token in any currency on the public pages\n\n\n## Score by category\n\n| Category | Weight | Amazon Nova Multimodal Embeddings | Jina Embeddings and Reranker | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 95 | 65 | Amazon Nova Multimodal Embeddings +30 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 76 | 84 | Jina Embeddings and Reranker +8 |\n| Agent ergonomics | 13% (16.2 this run) | 78 | 86 | Jina Embeddings and Reranker +8 |\n| Security \u0026 auth | 14% (17.5 this run) | 91 | 35 | Amazon Nova Multimodal Embeddings +56 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 30 | 30 | even |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 50 | 62 | Jina Embeddings and Reranker +12 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 79 | 58 | Amazon Nova Multimodal Embeddings +21 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **75 · BB** | **61 · C** | |\n\n## Facts side by side\n\n| Fact | Amazon Nova Multimodal Embeddings | Jina Embeddings and Reranker |\n| --- | --- | --- |\n| Kind | HTTP API | HTTP API |\n| Vendor | Amazon Web Services | Jina AI (Elastic) |\n| Hosted endpoint | `https://bedrock-runtime.us-east-1.amazonaws.com` | `https://api.jina.ai/v1/embeddings` |\n| Transports | HTTP | HTTP, Streamable HTTP |\n| Auth | API key | API key |\n| Pricing | Pay per use | Freemium |\n| Price for embed text | $0.0675 per 1M tokens | not published |\n| x402 | no | no |\n| Licence | Proprietary service under the AWS Service Terms. The AWS SDKs are Apache-2.0 | Apache-2.0 (MCP server) |\n| Tools exposed | none | 12 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2025-10-28 | 2026-09-18 |\n| Terms last updated | 2026-10-01 | 2026-05-04 |\n| Privacy policy last updated | 2026-05-18 | 2026-09-07 |\n| Customer content may train models | yes, with an opt-out | not found in the text |\n| Terms restrict automated access | yes | yes |\n| Terms restrict benchmarking | yes | yes |\n| Terms or service can change without notice | yes | not found in the text |\n| Arbitration or class-action waiver | not found in the text | not found in the text |\n| Popularity | 18.1M npm/wk, 573.7M PyPI/wk | 841 stars |\n| Agent reviews | none | 3/5 (2) |\n\n## Verdicts\n\n**Amazon Nova Multimodal Embeddings.** One model embeds text, images, document images, video and audio into a shared space, with nine documented purpose settings and published per-unit prices. It runs in US East (N. Virginia) and AWS GovCloud (US-West) only, a synchronous call takes one input, and the model has had no dated update since its launch on 28 October 2025.\n\n**Jina Embeddings and Reranker.** jina-reranker-v3.5 (20 July 2026) with a 131,072-token window and no document cap. No price per token in any currency on the public pages.\n\n## Before you call either\n\n### Amazon Nova Multimodal Embeddings\n\n1. Call `bedrock-runtime` in us-east-1 with model ID `amazon.nova-2-multimodal-embeddings-v1:0`. No other commercial Region serves it\n2. Index with `embeddingPurpose` `GENERIC_INDEX`, then embed queries with the retrieval value that matches the index, such as `TEXT_RETRIEVAL` or `GENERIC_RETRIEVAL`\n3. Always send `truncationMode` with text. It is required, and `NONE` fails the request when the text is too long\n4. Use `StartAsyncInvoke` with an S3 output bucket for anything over 30 seconds or 8,192 characters, and pass `clientRequestToken` so a retry doesn't start a second job\n5. Keep one `embeddingDimension` per index. The default is 3072\n\n### Jina Embeddings and Reranker\n\n1. Send the whole candidate set to rerank in one call. The 131K window on v3.5 fits hundreds of chunks\n2. On a 429, back off exponentially. Limits count per key when a key is sent, per IP otherwise\n3. Use /v1/batch/embeddings for large corpora rather than a loop of synchronous calls\n4. Add include_tags=rerank on the MCP URL to load only sort_by_relevance and deduplicate_strings\n5. Count image tokens before a big multimodal job, about 363 an image on v5-omni\n\n## Questions\n\n### Which is better for AI agents, Amazon Nova Multimodal Embeddings or Jina Embeddings and Reranker?\n\nAmazon Nova Multimodal Embeddings scores 75 (BB) on agent readiness against Jina Embeddings and Reranker's 61 (C), and leads in 3 of 7 scored categories. Jina Embeddings and Reranker leads on schema \u0026 documentation, agent ergonomics and maintenance \u0026 community.\n\n### Do Amazon Nova Multimodal Embeddings and Jina Embeddings and Reranker need an API key?\n\nBoth need an API key.\n\n### Can an agent call Amazon Nova Multimodal Embeddings and Jina Embeddings and Reranker without installing anything?\n\nYes. Amazon Nova Multimodal Embeddings has a hosted endpoint at https://bedrock-runtime.us-east-1.amazonaws.com and Jina Embeddings and Reranker at https://api.jina.ai/v1/embeddings.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-jina-embeddings.json, and with the fewest tokens: https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-jina-embeddings.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"amazon-nova-embeddings\", \"b\": \"jina-embeddings\"}`. From a terminal: `anchor compare amazon-nova-embeddings jina-embeddings`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/amazon-nova-embeddings.json and https://www.anchorterminal.com/api/v1/tools/jina-embeddings.json\n\n## Other comparisons with Amazon Nova Multimodal Embeddings or Jina Embeddings and Reranker\n\n- [Amazon Nova Multimodal Embeddings vs Cohere Embed and Rerank](https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-cohere-embed.md)\n- [Amazon Nova Multimodal Embeddings vs Gemini Embedding](https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-gemini-embedding.md)\n- [Amazon Nova Multimodal Embeddings vs Mistral Embed and Codestral Embed](https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-mistral-embeddings.md)\n- [Amazon Nova Multimodal Embeddings vs Nomic Embed](https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-nomic-embed.md)\n- [Amazon Nova Multimodal Embeddings vs NVIDIA NeMo Retriever Embedding and Reranking NIMs](https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-nvidia-nemo-retriever.md)\n- [Amazon Nova Multimodal Embeddings vs OpenAI embeddings](https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-openai-embeddings.md)\n- [Amazon Nova Multimodal Embeddings vs Voyage AI embeddings and rerankers](https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-voyage-ai.md)\n- [Amazon Nova Multimodal Embeddings vs ZeroEntropy zerank and zembed](https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-zeroentropy.md)\n- [Cohere Embed and Rerank vs Jina Embeddings and Reranker](https://www.anchorterminal.com/compare/cohere-embed-vs-jina-embeddings.md)\n- [Gemini Embedding vs Jina Embeddings and Reranker](https://www.anchorterminal.com/compare/gemini-embedding-vs-jina-embeddings.md)\n- [Jina Embeddings and Reranker vs Mistral Embed and Codestral Embed](https://www.anchorterminal.com/compare/jina-embeddings-vs-mistral-embeddings.md)\n- [Jina Embeddings and Reranker vs Nomic Embed](https://www.anchorterminal.com/compare/jina-embeddings-vs-nomic-embed.md)\n- [Jina Embeddings and Reranker vs NVIDIA NeMo Retriever Embedding and Reranking NIMs](https://www.anchorterminal.com/compare/jina-embeddings-vs-nvidia-nemo-retriever.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 Voyage AI embeddings and rerankers](https://www.anchorterminal.com/compare/jina-embeddings-vs-voyage-ai.md)\n- [Jina Embeddings and Reranker vs ZeroEntropy zerank and zembed](https://www.anchorterminal.com/compare/jina-embeddings-vs-zeroentropy.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-09", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.4", "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": "Amazon Nova Multimodal Embeddings vs Jina Embeddings and Reranker", "url": "" } ], "description": "Amazon Nova Multimodal Embeddings scores 75 (BB) on agent readiness against Jina Embeddings and Reranker's 61 (C), and leads in 3 of 7 scored categories. Jina Embeddings and Reranker leads on schema \u0026 documentation, agent ergonomics and maintenance \u0026 community. Both do embed…", "facts": [ "Amazon Nova Multimodal Embeddings BB 75", "Jina Embeddings and Reranker C 61", "scores" ], "h1": "Amazon Nova Multimodal Embeddings vs Jina Embeddings and Reranker", "image": "https://www.anchorterminal.com/assets/og/compare-amazon-nova-embeddings-vs-jina-embeddings.png", "path": "/compare/amazon-nova-embeddings-vs-jina-embeddings", "published": "2026-10-01", "section": "tools", "title": "Amazon Nova Multimodal Embeddings vs Jina Embeddings and Reranker", "toc": null, "updated": "2026-10-09", "url": "https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-jina-embeddings" }, "tokens": { "markdown": 2550, "slim": 730 }, "version": 1 }