{ "data": { "a": { "slug": "antseed", "name": "Antseed", "vendor": "Antseed Foundation", "vendorUrl": "https://antseed.com", "kind": "router", "category": "inference", "summary": "Antseed is an open-source peer-to-peer network for buying and selling AI inference. A buyer runs a local proxy with OpenAI and Anthropic format endpoints, which routes each request to an independent seller and pays in USDC on Base.", "url": "https://www.anchorterminal.com/tools/antseed", "markdownUrl": "https://www.anchorterminal.com/tools/antseed.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/antseed.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/antseed.json", "dns": "antseed.grade.anchorterminal.com", "repo": "https://github.com/Antseed/antseed", "license": "GPL-3.0 (LICENSE in the repository). The @antseed/cli manifest on npm carries no licence field", "transports": [ "http" ], "packages": [ { "registry": "npm", "name": "@antseed/cli" } ], "auth": "none", "authNotes": "No account and no API key. The local proxy at 127.0.0.1:8377 doesn't check a key, so clients that need one send a placeholder such as `antseed-p2p`. Identity is a secp256k1 key the CLI creates on first run. Its EVM address is the peer id and the paying wallet. A public tunnel or the gateway (`antseed gateway`, `antseed tunnel start`) needs a generated `antseed_...` bearer key, with optional spend limits and expiry per key.", "pricing": "usage", "pricingNotes": "Sellers set their own prices per 1M input, cached-input and output tokens, published without login per PRICING.md and readable live with `antseed network browse --json`. Buyers pre-deposit USDC on Base and pay per request. Some models are free. The FAQ sets network fees at 4 per cent, and a gasless deposit costs a fixed $0.05 relay fee. The software is free.", "priceSummary": "4% fee", "where": "local", "x402": { "level": "no", "evidence": "Inference isn't paid by x402. Sellers answer HTTP 402 and the buyer signs Antseed's own EIP-712 ReserveAuth and SpendingAuth against an on-chain USDC channel (https://antseed.com/blog/the-402-flow/). x402 v2 appears only on `POST /v1/key/topup` of a gateway the owner runs, off until enabled per key (CHANGELOG.md, checked 2026-10-08).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 106, "npmWeekly": 1823, "pypiWeekly": null, "asOf": "2026-10-08" }, "docsUrl": "https://antseed.com/docs/", "llmsTxt": "https://antseed.com/llms.txt", "capabilities": [ "inference.router", "inference.llm" ], "tags": [ "open-source", "local", "p2p", "usdc", "base", "no-signup", "no-card", "openai-compatible", "anthropic-compatible", "llms-txt", "cli", "desktop", "pre-1.0" ], "lastRelease": "2026-10-31", "graded": true, "anchor": { "graded": true, "score": 54.1, "grade": "C", "agentReady": false, "rank": 921, "ranked": true, "rankOf": 1510, "categoryRank": 27, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 56, "maintenance": 79, "payments": 70, "reliability": 52, "schema": 55, "security": 45, "transparency": 59 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-04" }, "negative": -3, "negativeNotes": [ "2026-10-12. The buyer proxy forwarded a client's `Authorization`, `x-api-key`, cookie and other credential headers to the seller it routed to, a flaw the repository's own review of 8 March 2026 lists as VULN-002 and issue #1104 (4 October 2026) raised. Commit 6d2c7c13 stopped it, first released in v0.2.58 on 12 October 2026, and CHANGELOG.md marks the entry as security and tells users to rotate exposed keys. Two more released fixes marked security in CHANGELOG.md fold into the same term, a local client spending from a workspace wallet by naming its buyer identity (v0.2.61, 16 October 2026) and API-key holders reusing a request ID to skip spend accounting (v0.2.67, 22 October 2026). No published advisory was found on osv.dev, so the released fixes without an advisory take -3. https://github.com/Antseed/antseed/blob/main/CHANGELOG.md" ], "verdict": "A buyer needs no account. The CLI creates a wallet key, free models answer at once and paid ones draw on deposited USDC, with seller, tokens and cost in response headers. Sellers are unvetted and can read prompts unless TEE-verified, the proxy forwarded client credentials to them until 12 October 2026 with no advisory, and every package is pre-1.0.", "bestFor": "Agents and coding tools that want pay-per-request inference with no account, and owners comfortable holding USDC on Base.", "strengths": [ "No sign-up. `npm install -g @antseed/cli` and `antseed buyer start` give a local endpoint at http://localhost:8377, and some models are free", "One proxy accepts Anthropic Messages, OpenAI Chat Completions and OpenAI Responses requests and translates between them when the seller speaks another format", "PRICING.md says seller prices per 1M tokens are published with no login, and `antseed network browse --json` reads them live", "Non-streaming responses carry `x-antseed-peer-id`, token counts and `x-antseed-estimated-cost-usd`, and `antseed buyer metering` gives totals per channel", "GPL-3.0 source, CI on main and 67 tagged releases between 6 August and 31 October 2026" ], "weaknesses": [ "The buyer proxy copied client credential headers to sellers until v0.2.58 (12 October 2026), with no published advisory", "Sellers are independent and unvetted. The FAQ says a standard seller can read the prompt it serves, and each sets its own data practices", "Pre-1.0 everywhere. Release tag v0.2.72 carries CLI 0.1.220, and CHANGELOG.md keeps recent entries under one Unreleased heading", "No OpenAPI document, security.txt, SECURITY.md, published advisory, bug bounty or contract audit report was found", "The buyer key is also the wallet, and the CLI stores it in plain text at ~/.antseed/identity.key unless `ANTSEED_IDENTITY_HEX` is set" ], "agentNotes": [ "Send a placeholder key such as `antseed-p2p`, and run v0.2.58 or later, which stops credential headers reaching sellers.", "Call `GET /v1/models` first and request a concrete id. The `antseed` alias works only when the desktop app has a model selected", "Handle 402 `insufficient_deposits` by reading `suggestedAmount`, then fund the address from `antseed buyer deposit` with USDC on Base", "Pass `--verifiers antseed-verifier --require-verifier` to `antseed buyer start` when prompts are private, so only TEE-verified sellers are routed", "Read `x-antseed-peer-id` and `x-antseed-estimated-cost-usd` on each response, and pin a seller with `\u003cpeerId\u003e@\u003cmodel\u003e` when the same one must answer" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 54.1 } ], "editorialScores": { "ergonomics": 56, "maintenance": 79, "payments": 70, "reliability": 52, "schema": 55, "security": 45, "transparency": 66 }, "provenanceScore": 52, "checked": { "categories": { "ergonomics": "2026-11-04", "maintenance": "2026-11-04", "payments": "2026-11-04", "reliability": "2026-11-04", "schema": "2026-11-04", "security": "2026-11-04", "transparency": "2026-11-04" }, "last": "2026-11-04", "lastMoved": "2026-11-04", "oldest": "2026-11-04", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "npm install -g @antseed/cli \u0026\u0026 antseed buyer start", "http": "curl http://localhost:8377/v1/chat/completions -H 'content-type: application/json' -d '{\"model\": \"deepseek-v4-flash\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello\"}]}'" }, "letme": { "capability": "https://letme.dev/inference.router", "tool": "https://letme.dev/antseed" }, "area": "models", "unitPrices": [ { "item": "Network fee", "unit": "pct", "usd": 4, "note": "Per the FAQ. Model prices are set by each seller" }, { "item": "Gasless deposit relay", "unit": "tx", "usd": 0.05, "note": "Fixed fee per sweep on Base mainnet" } ], "provenance": { "legalEntity": "Antseed Foundation", "domain": "antseed.com", "domainRegistered": "2026-02-23", "endpointOnVendorDomain": null, "terms": "https://antseed.com/terms-of-service/", "privacy": "", "statusPage": "", "changelog": "https://github.com/Antseed/antseed/blob/main/CHANGELOG.md", "securityTxt": "none", "checked": "2026-11-04", "notes": [ "The site footer reads © 2026 Antseed Foundation. The foundation post of 17 July 2026 calls it a non-profit and gives no jurisdiction or registration number.", "The terms (last updated 9 October 2026, Gibraltar law) say the protocol is not a company and that supporting entities don't operate or control the network. Their contact section points to the repository's issues.", "https://antseed.com/privacy/ is a product page about anonymity, not a privacy policy. Section 16 of the terms covers data, and docs/telemetry.md in the repository covers the desktop app.", "The endpoint an agent calls is on the owner's machine. The price snapshot is at network.antseed.com, and https://antseed.com/network shows live network data with no incident history.", "antseed.com/.well-known/security.txt and /security.txt both returned 404 on 8 October, and the repository has no SECURITY.md on 4 November.", "RDAP gives 2026-02-23 as the registration date for antseed.com. @antseed/cli was first published to npm on 2026-02-24.", "The terms bar using software, automated agents or scripts to scrape or mine data from the Offerings, defined to include the documentation, so antseed.com and network.antseed.com beyond the terms were not read on 4 November." ], "score": 52 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/antseed.json", "live": { "slug": "antseed", "versions": [ { "registry": "github", "name": "Antseed/antseed", "version": "v0.2.75", "released": "2026-11-06", "seenAt": "2026-11-06T23:06:26.206621872Z" }, { "registry": "npm", "name": "@antseed/cli", "version": "0.1.233", "seenAt": "2026-11-06T23:06:25.971132423Z" } ], "githubStars": 134, "npmWeekly": 3937, "securityTxt": { "url": "https://antseed.com/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-07T16:00:21.529216902Z" }, "llmsTxt": { "url": "https://antseed.com/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:31:33.843590794Z" }, "domain": { "domain": "antseed.com", "registered": "2026-02-23", "source": "https://rdap.verisign.com/com/v1/domain/antseed.com", "checkedAt": "2026-11-01T14:07:44.278290475Z" }, "pages": [ { "url": "https://raw.githubusercontent.com/Antseed/antseed/main/CHANGELOG.md", "kind": "changelog", "status": 200, "checkedAt": "2026-11-07T14:17:56.702739614Z", "changedAt": "2026-11-07T14:17:56.702739614Z", "fingerprint": "15d8d4afbfb5" }, { "url": "https://antseed.com/terms-of-service/", "kind": "terms", "status": 200, "checkedAt": "2026-11-07T13:59:09.334745665Z", "changedAt": "2026-10-29T04:58:31.310358429Z", "fingerprint": "9c5799bf23b1" } ], "github": { "repo": "antseed/antseed", "checkedAt": "2026-11-02T08:31:03.445259855Z", "stars": 132, "archived": false, "issuesEnabled": true, "pushedAt": "2026-11-02T02:30:59Z", "openIssues": 76, "openPRs": 47, "issuesOpened90d": 109, "issuesClosed90d": 55, "prsMerged90d": 435, "ci": { "branch": "main", "runs": 50, "success": 50, "failure": 0, "other": 0, "latest": "success", "latestAt": "2026-11-01T03:43:44Z" }, "replies": { "sampled": 25, "unanswered": 22, "medianDays": 0.4 } }, "updatedAt": "2026-11-07T16:00:21.529216902Z" } }, "answer": "Vertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against Antseed's 54.1 (C), and leads in 6 of 7 scored categories. Antseed leads on payments \u0026 pricing.", "b": { "slug": "vertex-ai", "name": "Vertex AI (Gemini Enterprise Agent Platform)", "vendor": "Google Cloud", "vendorUrl": "https://cloud.google.com/products/gemini-enterprise-agent-platform", "kind": "model", "category": "inference", "summary": "Google Cloud's enterprise API for Gemini models and Model Garden partner and open models, including Claude, Llama and Qwen, on the platform formerly called Vertex AI, with regional endpoints, provisioned throughput and IAM access.", "url": "https://www.anchorterminal.com/tools/vertex-ai", "markdownUrl": "https://www.anchorterminal.com/tools/vertex-ai.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/vertex-ai.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/vertex-ai.json", "dns": "vertex-ai.grade.anchorterminal.com", "repo": "https://github.com/googleapis/python-genai", "license": "Proprietary service under the Google Cloud Platform terms. Partner models carry their providers' terms. The Google Gen AI SDKs are Apache-2.0", "transports": [ "http" ], "remoteUrl": "https://aiplatform.googleapis.com/v1", "packages": [ { "registry": "pypi", "name": "google-genai" }, { "registry": "npm", "name": "@google/genai" }, { "registry": "pypi", "name": "google-cloud-aiplatform" } ], "auth": "mixed", "authNotes": "OAuth 2.0 bearer tokens from application default credentials or service accounts, with IAM roles on a Google Cloud project, which the docs recommend for production. Google Cloud API keys, including express mode keys (Preview) that need no project or location in the URL, are recommended for testing. The OpenAI-compatible endpoint accepts only Google Cloud auth.", "pricing": "usage", "pricingNotes": "Per-token prices per model, with global and higher non-global rates and Standard, Priority and Flex/Batch options. Gemini 4 Argon costs $4/$20 per million, with 50% credits back through 2026-11-30. Gemini 3.8 Flash costs $0.75/$3.75 through 2026-12-31, then $1.50/$7.50. Claude Opus 5.5 $4/$20. Batch and Flex half price on Gemini. Only requests that return 200 are charged. Express mode gives new users 90 days free with no billing details (https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing).", "priceSummary": "from $0.30 / 1M in", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 on the pricing page or in the express mode docs (checked 2026-11-06). Access needs a Google account and, after the express trial, a Cloud billing account.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": 20917051, "asOf": "2026-11-06" }, "docsUrl": "https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/start", "rateLimitsUrl": "https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/standard-paygo", "openapi": "https://aiplatform.googleapis.com/$discovery/rest?version=v1", "capabilities": [ "inference.llm", "inference.open-weights" ], "tags": [ "official", "hosted", "model", "open-weights", "enterprise", "usage-priced", "free-tier", "no-card", "python", "typescript", "status-page" ], "lastRelease": "2026-11-05", "graded": true, "anchor": { "graded": true, "score": 88.7, "grade": "AA", "agentReady": true, "rank": 2, "ranked": true, "rankOf": 1510, "categoryRank": 1, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 97, "maintenance": 91, "payments": 40, "reliability": 99, "schema": 94, "security": 97, "transparency": 90 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-06" }, "negative": 0, "verdict": "Gemini, Claude and open models through one Google Cloud API with IAM, regional endpoints, schema-guaranteed JSON and a 99.5 per cent SLA, and no Vertex incident on the Cloud status page in the 90 days to 6 November 2026. Gemini 4 Argon and 3.8 Flash have 12-month availability, but short-term Flash models get a 95 per cent SLA.", "bestFor": "Google Cloud customers who need Gemini with residency, VPC-SC, provisioned throughput and an SLA, or Claude under a Google bill.", "strengths": [ "No incident naming Vertex or Gemini on status.cloud.google.com between 8 July and 6 October 2026", "Public discovery document for the v1 API (revision 20260930) with 1,128 methods and 1,493 schemas", "JSON output follows a supplied `response_schema` when `response_mime_type` is `application/json`", "Express mode gives new users 90 days free with an API key and no billing details", "Only requests that return 200 are charged", "Gemini 4 Argon, GA since 13 October 2026, has a 1,048,576-token unified limit at $4/$20 per million tokens" ], "weaknesses": [ "The SLA drops from 99.5 to 95 per cent for short-term availability models, Gemini 3.7 and 3.6 Flash among them", "Gemini 3.6 Flash, released 21 July 2026, retires on 19 November 2026, and 3.7 Flash on 28 January 2027", "Zero retention needs an exception request, and flagged prompts may be kept up to 90 days", "The Interactions API stores prompts and responses unless `store` is set to false", "No llms.txt on the docs site, and the docs mix the Vertex AI and Agent Platform names", "The model versions table still listed Gemini 2.5 Pro, Flash and Flash-Lite as available after their 20 October 2026 retirement date" ], "agentNotes": [ "Call the `global` location on aiplatform.googleapis.com unless data residency requires a Region. The 429 guide says it spreads load and reduces errors", "Back off exponentially on 429 `Resource exhausted`. On Standard PayGo it means shared capacity is busy, not a fixed quota", "Send `response_schema` with `response_mime_type: application/json`. JSON mode alone doesn't guarantee valid output", "Set `store` to false on Interactions API calls. It defaults to true and keeps prompts and responses", "Pin `gemini-4-argon` or `gemini-3.8-flash`, both in the 12-month tier, rather than 3.7 or 3.6 Flash, which retire on 28 January 2027 and 19 November 2026" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "AA", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 88.7 } ], "editorialScores": { "ergonomics": 97, "maintenance": 91, "payments": 40, "reliability": 99, "schema": 94, "security": 97, "transparency": 83 }, "provenanceScore": 97, "checked": { "categories": { "ergonomics": "2026-11-06", "maintenance": "2026-11-06", "payments": "2026-11-06", "reliability": "2026-11-06", "schema": "2026-11-06", "security": "2026-11-06", "transparency": "2026-11-06" }, "last": "2026-11-06", "oldest": "2026-11-06", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install google-genai # or: npm i @google/genai", "http": "curl -X POST \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $(gcloud auth print-access-token)\" \\\n \"https://aiplatform.googleapis.com/v1/projects/${GOOGLE_CLOUD_PROJECT}/locations/global/publishers/google/models/gemini-3.8-flash:generateContent\" \\\n -d '{\"contents\":{\"role\":\"user\",\"parts\":{\"text\":\"Explain how AI works in a few words\"}}}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/vertex-ai" }, "sameCompany": [ "gemini-api", "gemini-embedding", "vertex-ai-tuning", "cloud-run-gpus", "google-model-armor", "google-imagen", "google-veo", "google-lyria", "google-speech-to-text", "google-cloud-tts", "gemini-live", "google-adk", "google-memory-bank", "google-secret-manager", "google-cloud-document-ai", "google-weather-api", "chrome-devtools-mcp", "google-maps-platform", "google-cloud-translation", "google-calendar-api", "firebase-cloud-messaging", "google-cloud-storage", "google-drive-api", "gemini-enterprise", "gemini-cli", "google-search-console", "google-ads-api", "google-forms", "google-sheets-api", "gmail-api", "google-people-api" ], "area": "models", "unitPrices": [ { "item": "Grounding with Google Search over 5,000 a month (Gemini 3)", "unit": "1k-requests", "usd": 14 } ], "provenance": { "legalEntity": "Google LLC", "domain": "google.com", "domainRegistered": "1997-09-15", "domainNote": "The endpoint is on googleapis.com, Google's API domain. google.com was registered in 1997.", "endpointOnVendorDomain": true, "terms": "https://cloud.google.com/terms", "privacy": "https://policies.google.com/privacy", "statusPage": "https://status.cloud.google.com", "changelog": "https://docs.cloud.google.com/gemini-enterprise-agent-platform/release-notes", "securityTxt": "valid", "checked": "2026-11-06", "notes": [ "The product runs under the Google Cloud Platform terms, whose contracting Google entity depends on the billing country, as for vertex-ai-tuning.", "www.google.com/.well-known/security.txt expires on 2030-04-01 (read 2026-11-06).", "docs.cloud.google.com has no llms.txt (404 on 6 October 2026), but each docs page answers as Markdown when `.md.txt` is added to its URL." ], "score": 97 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/vertex-ai.json", "live": { "slug": "vertex-ai", "probe": { "target": "https://aiplatform.googleapis.com/v1", "method": "get", "lastAt": "2026-11-07T19:22:43.041024218Z", "lastOk": true, "lastStatus": 404, "lastMs": 664, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 118, "p95ms24h": 752, "samples24h": 210, "samples30d": 210, "days": [ { "date": "2026-11-06", "probes": 13, "ok": 13 }, { "date": "2026-11-07", "probes": 197, "ok": 197 } ] }, "versions": [ { "registry": "github", "name": "googleapis/python-genai", "version": "v3.0.0", "released": "2026-11-06", "seenAt": "2026-11-07T00:15:33.519504561Z" }, { "registry": "npm", "name": "@google/genai", "version": "3.0.0", "seenAt": "2026-11-07T00:15:31.639429892Z" }, { "registry": "pypi", "name": "google-cloud-aiplatform", "version": "2.7.0", "released": "2026-10-28", "seenAt": "2026-11-07T00:15:32.521225598Z" }, { "registry": "pypi", "name": "google-genai", "version": "3.0.0", "released": "2026-11-06", "seenAt": "2026-11-07T00:15:31.485691571Z" } ], "githubStars": 4057, "npmWeekly": 31989360, "pypiWeekly": 38431674, "securityTxt": { "url": "https://google.com/.well-known/security.txt", "state": "valid", "expires": "2030-04-01T00:00:00z", "checkedAt": "2026-11-07T16:01:22.068349931Z" }, "pages": [ { "url": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-07T14:01:16.257808105Z", "changedAt": "2026-11-07T14:01:16.257808105Z", "fingerprint": "a4fe253bd23f" } ], "updatedAt": "2026-11-07T19:22:43.041024218Z" } }, "edges": [ { "by": 52, "category": "security", "leads": "vertex-ai", "name": "Security \u0026 auth", "reasons": { "a": "Model reading. The local proxy has no key and binds to 127.0.0.1. One secp256k1 key is identity and wallet, stored in plain text by the CLI unless supplied by environment variable, and encrypted by the OS keychain in the desktop app. Spending is bounded by a deposit contract, a capped ReserveAuth per seller and an optional separate withdrawal wallet, and gateway keys are hashed, revocable and spend-limited (18 of 30). Sellers are independent, and the FAQ says a standard seller can read prompts and sets its own practices (5 of 20). No central log, and an optional TEE-verified route with attestation checked on the buyer's machine (8 of 15). Seller, token and cost headers per response, `antseed buyer metering` and a Prometheus exporter (12 of 15). The buyer proxy stopped forwarding client credentials to sellers in v0.2.58 (12 October 2026). No SECURITY.md in the 4 November clone; no security.txt, published advisory, bug bounty, certification or contract audit report found. The repository holds one automated review of the buyer proxy dated 8 March 2026 (2 of 20). Docs per the 8 October check, not re-read on 4 November, because the terms of 9 October 2026 bar scripts that scrape or mine data from the Offerings, which include the documentation.", "b": "Model reading. OAuth 2.0 with IAM roles and service accounts, which the docs recommend for production, with API keys for testing. No key in a query string found in the docs we read (30). The training restriction in the Service Specific Terms says Google won't use customer data to train or fine-tune any model without permission, GA and pre-GA alike (20). Default in-memory caching for 24 hours that can be disabled, flagged prompts logged up to 90 days unless an abuse-monitoring exception is granted or the customer has a Cloud Master Agreement, the Interactions API storing by default, and Claude Fable 5 and Mythos 5 requiring 30-day retention shared with Anthropic (12 of 15, a judgement call matching the Fable exception on the Anthropic and Bedrock listings). Cloud Audit Logs, with Data Access logs off until enabled, and optional request-response logging to BigQuery (15). google.com security.txt valid to 2030-04-01, the Google VRP, and Generative AI on the platform in ISO 27001, 27017 and 27018 and SOC 1, 2 and 3 scope per the 1 October services-in-scope check for vertex-ai-tuning, not re-read on 6 October (20)." }, "scores": { "a": 45, "b": 97 } }, { "by": 47, "category": "reliability", "leads": "vertex-ai", "name": "Reliability", "reasons": { "a": "Read with the local-software lines, since the buyer runs the proxy. Official npm package @antseed/cli with Node.js 20 or later stated, plus desktop installers (20). Public CI on main runs the unit tests, an end-to-end suite and a payment flow (ci.yml in the clone), but the run results on GitHub couldn't be read on 4 November, so 15 of 25. Open issues and pull requests per the 8 October count (74 and 32), with bug reports from late September open then and reply times not sampled (12 of 25). CHANGELOG.md calls out breaking CLI changes, but versions are 0.x patch bumps and recent entries sit under one Unreleased heading (5 of 15). Release tag v0.2.72 and CLI 0.1.220 at that tag, with no statement of stability (0). Whether a request is answered also depends on which sellers are online, which this checklist doesn't score.", "b": "Google Cloud status dashboard with per-product history (20). Its incident feed, read on 6 November, has no incident naming Vertex Gemini API, Gemini or the Agent Platform in the 90 days. The regional incidents of 20 August, 1 September and 20 October (europe-west2) and the Cloud Storage incident of 8 and 9 October didn't list it among affected products (30). Standard PayGo publishes usage tiers by 30-day spend with baseline throughput, 2,000,000 to 50,000,000 tokens a minute for Flash models and 500,000 to 10,000,000 for Pro, plus quota tables for other methods (15). A 429 page says to use the global endpoint and truncated exponential backoff, and a retry-strategy page (15). SLA of 99.5 per cent a month on generateContent and streamGenerateContent, 95 per cent for short-term availability models, and a latency SLO on Provisioned Throughput. The 429 page says pay-as-you-go 429s don't count toward the SLA error rate (10). Gemini 4 Argon reached GA on 13 October and Gemini 3.8 Flash moved to the 12-month tier, and the v1 API, 3.5 Flash-Lite and Claude Opus 5.5 are GA, but express mode was Preview at the 6 October check (9 of 10, up from 8). Up from 98 on 6 October." }, "scores": { "a": 52, "b": 99 } }, { "by": 41, "category": "ergonomics", "leads": "vertex-ai", "name": "Agent ergonomics", "reasons": { "a": "Model reading, as for other routers. Tool use and structured output depend on the seller, and the model list reports both per seller with conservative model-level values (12 of 20 and 8 of 15). Cached-input pricing is advertised per seller where supported (8 of 15). Context length is reported per model as the lowest value across sellers (10 of 15). No batch route found (0 of 10). No SDK of its own for buyers. OpenAI and Anthropic SDKs work against the proxy, and wrappers launch Claude Code, Codex and OpenCode (5 of 10). Documented error codes with fixes, and cost and seller headers on non-streaming responses (13 of 15). Docs per the 8 October check, not re-read on 4 November, because the terms of 9 October 2026 bar scripts that scrape or mine data from the Offerings, which include the documentation.", "b": "Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Function calling with `FunctionCallingConfig` mode ANY and `allowedFunctionNames` to force a named tool (20). Schema-guaranteed JSON output (15). Implicit and explicit context caching, cached input at 0.1x, $0.075 per million on 3.8 Flash through 31 December (15). 1,048,576-token context on 3.8 Flash, a unified 1,048,576-token input and output limit on Gemini 4 Argon, and 1,000,000 on Claude Opus 5.5 (15). Flex/Batch at half price on Gemini (10). Gen AI SDKs for Python and JavaScript among others, and the OpenAI libraries work with Google Cloud auth (10). 429 handling documented per quota framework, with standard Google status codes elsewhere (12 of 15)." }, "scores": { "a": 56, "b": 97 } }, { "by": 39, "category": "schema", "leads": "vertex-ai", "name": "Schema \u0026 documentation", "reasons": { "a": "No OpenAPI document found in the repository or docs. The proxy copies the OpenAI and Anthropic wire formats (0 of 25). llms.txt at antseed.com/llms.txt and a setup skill at /skill.md (10). The API guide states what each route is for, how routing picks a seller and when to pin one (14 of 20). Request bodies follow the upstream formats, and `/v1/models` reports context length, modalities, tool use and supported parameters per seller (8 of 15). Curl examples for each format and an error table with status, code, meaning and fix (13 of 15). A public changelog and tagged releases, with recent entries under an undated Unreleased heading (10 of 15). Docs per the 8 October check, not re-read on 4 November, because the terms of 9 October 2026 bar scripts that scrape or mine data from the Offerings, which include the documentation.", "b": "Model reading. Keyless discovery document for the Agent Platform API v1, revision 20260930, with 1,128 methods and 1,493 schemas (25). No llms.txt, but every docs page answers as Markdown at `.md.txt`, counted as for vertex-ai-tuning (10). Model cards give limits, capabilities and retirement dates, and the 3.8 Flash card says when to use 3.7 Flash instead, but the docs mix the Vertex AI and Agent Platform names, and the OpenAI page tells new users to call the Gemini Developer API instead (16 of 20). Structured output with `response_schema` and `response_mime_type: application/json` always follows the schema per the docs, and complex schemas fail with a 400 (15). Examples on every page and a 429 guide, but we found no full error code list for generateContent (13 of 15). Versioned v1 and v1beta1 APIs and release notes with entries on most working days, newest 5 November 2026 (15)." }, "scores": { "a": 55, "b": 94 } }, { "by": 31, "category": "transparency", "leads": "vertex-ai", "name": "Transparency \u0026 trust", "reasons": { "a": "GPL-3.0 source for the protocol, CLI, desktop app and contracts (30). The terms (last updated 9 October 2026), FAQ and privacy page agree that there is no central request log and that sellers may log prompts. There is no privacy policy document, and docs/telemetry.md says the PostHog region and retention period are still to be documented (12 of 30). No deprecation policy found. The changelog gives version cut-offs for protocol changes and a dated cutover of 10 September 2026 for staking contracts (8 of 20). Desktop telemetry is documented event by event with a toggle and an environment switch, and is keyed to the buyer's public wallet address. No telemetry code found in the CLI (16 of 20). docs/telemetry.md is unchanged since 15 September 2026 in the 4 November clone.", "b": "Closed service under the Google Cloud terms, with the Gen AI SDKs under Apache-2.0 and a public discovery document (18, as for Bedrock's open service models). The zero data retention and abuse monitoring pages agree with the Cloud terms and give periods for each case, 24 hours in memory, up to 90 days for flagged prompts, 30 days for Advanced AI models, 3 days for Search grounding logs and 30 days for Maps grounding, and say which can't be switched off (27 of 30). A dated model versions table with release and retirement dates and a stated 12-month or 45-day policy, but on 6 November it still listed Gemini 2.5 Pro, Flash and Flash-Lite as available with a 20 October 2026 retirement date and left them out of the retired table (18 of 20, down from 20). The Cloud subprocessor list with locations, per the 1 October vertex-ai-tuning check, regional and multi-region endpoints, and per-model ML processing locations on the partner model cards (20)." }, "scores": { "a": 59, "b": 90 } }, { "by": 30, "category": "payments", "leads": "antseed", "name": "Payments \u0026 pricing", "reasons": { "a": "x402 v2 exists only on `POST /v1/key/topup` of a gateway the owner runs, and is off until enabled per key. Inference is paid through Antseed's own HTTP 402 flow with EIP-712 signatures and USDC channels on Base, which isn't one of the three protocols the rubric names (10 of 40, a judgement call). PRICING.md in the repository says seller prices per 1M tokens are published without authentication at a cached endpoint and live through `antseed network browse --json` (20); the 8 October snapshot figures came from that JSON endpoint and are struck. Free models answer with no card and no account, per the docs on 8 October (20). An agent can install the CLI, get a key generated locally and fund it by a USDC transfer, with no sign-up flow (20). The self-hosted rule gives the same three lines for the free software.", "b": "No x402, MPP or L402 (0). Per-token prices per model and option published without a login (20). Express mode gives new Google Cloud users 90 days free within quotas with no billing details, though it's in Preview and needs a @gmail.com account (20). A person signs up in the console to get the express key (0)." }, "scores": { "a": 70, "b": 40 } } ], "facts": [ { "a": "Model router", "b": "Model API", "name": "Kind" }, { "a": "Antseed Foundation", "b": "Google Cloud", "name": "Vendor" }, { "a": "no (local only)", "b": "https://aiplatform.googleapis.com/v1", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "None", "b": "OAuth or key", "name": "Auth" }, { "a": "Pay per use", "b": "Pay per use", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "GPL-3.0 (LICENSE in the repository). The @antseed/cli manifest on npm carries no licence field", "b": "Proprietary service under the Google Cloud Platform terms. Partner models carry their providers' terms. The Google Gen AI SDKs are Apache-2.0", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "no", "name": "llms.txt" }, { "a": "2026-10-31", "b": "2026-11-05", "name": "Last release" }, { "a": "2026-05-15", "b": "2026-09-02", "name": "Terms last updated" }, { "a": "no document linked", "b": "2026-10-01", "name": "Privacy policy last updated" }, { "a": "not found in the text", "b": "yes", "name": "Customer content may train models" }, { "a": "not found in the text", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "not found in the text", "b": "not found in the text", "name": "Terms restrict benchmarking" }, { "a": "not found in the text", "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": "106 stars, 1.8k npm/wk", "b": "20.9M PyPI/wk", "name": "Popularity" } ], "faq": [ { "answer": "Vertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against Antseed's 54.1 (C), and leads in 6 of 7 scored categories. Antseed leads on payments \u0026 pricing.", "question": "Which is better for AI agents, Antseed or Vertex AI (Gemini Enterprise Agent Platform)?" }, { "answer": "Antseed needs no key. Vertex AI (Gemini Enterprise Agent Platform) takes an API key or an OAuth sign-in.", "question": "Do Antseed and Vertex AI (Gemini Enterprise Agent Platform) need an API key?" }, { "answer": "No hosted endpoint is listed for Antseed. Vertex AI (Gemini Enterprise Agent Platform) has a hosted endpoint at https://aiplatform.googleapis.com/v1.", "question": "Can an agent call Antseed and Vertex AI (Gemini Enterprise Agent Platform) without installing anything?" }, { "answer": "Antseed is open source (GPL-3.0 (LICENSE in the repository). The @antseed/cli manifest on npm carries no licence field). No open-source release is listed for Vertex AI (Gemini Enterprise Agent Platform).", "question": "Are Antseed and Vertex AI (Gemini Enterprise Agent Platform) open source?" } ], "goodFor": [ { "aheadOn": [ "Payments \u0026 pricing, 70 against 40" ], "also": [ "No key needed to call it", "Open source" ], "goodFor": "Agents and coding tools that want pay-per-request inference with no account, and owners comfortable holding USDC on Base.", "slug": "antseed", "watchFor": "The buyer proxy copied client credential headers to sellers until v0.2.58 (12 October 2026), with no published advisory" }, { "aheadOn": [ "Reliability, 99 against 52", "Schema \u0026 documentation, 94 against 55", "Agent ergonomics, 97 against 56", "Security \u0026 auth, 97 against 45", "Maintenance \u0026 community, 91 against 79", "Transparency \u0026 trust, 90 against 59" ], "also": [ "Agent-ready, a grade of BB or better", "A hosted endpoint, with nothing to install", "No incidents deducted, where Antseed loses 3 points for them" ], "goodFor": "Google Cloud customers who need Gemini with residency, VPC-SC, provisioned throughput and an SLA, or Claude under a Google bill.", "slug": "vertex-ai", "watchFor": "The SLA drops from 99.5 to 95 per cent for short-term availability models, Gemini 3.7 and 3.6 Flash among them" } ], "history": { "antseed": [ { "causes": [ "security", "evidence" ], "date": "2026-11-04", "delta": -1, "from": 55.1, "fromGrade": "C", "to": 54.1, "toGrade": "C" } ], "vertex-ai": null }, "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-antseed.json", "title": "Amazon Bedrock vs Antseed", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-antseed" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-vertex-ai.json", "title": "Amazon Bedrock vs Vertex AI (Gemini Enterprise Agent Platform)", "url": 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"title": "Muse Spark Open vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-vertex-ai.json", "title": "Novita AI vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-vertex-ai.json", "title": "OpenAI API vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/openai-api-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/openrouter-vs-vertex-ai.json", "title": "OpenRouter vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/openrouter-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/prism-inference-vs-vertex-ai.json", "title": "Prism Inference vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/prism-inference-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/ramp-router-vs-vertex-ai.json", "title": "Router.com (Ramp Router) vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/ramp-router-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-vertex-ai.json", "title": "Beam 1.0 vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/routerplus-vs-vertex-ai.json", "title": "RouterPlus vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/routerplus-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/sambanova-vs-vertex-ai.json", "title": "SambaCloud vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/sambanova-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/siliconflow-vs-vertex-ai.json", "title": "SiliconFlow vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/siliconflow-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/simplismart-vs-vertex-ai.json", "title": "Simplismart vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/simplismart-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/stepfun-api-vs-vertex-ai.json", "title": "StepFun API vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/stepfun-api-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/swe-2-flash-vs-vertex-ai.json", "title": "SWE-2 Flash vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/swe-2-flash-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/tencent-tokenhub-vs-vertex-ai.json", "title": "Tencent Cloud TokenHub vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/tencent-tokenhub-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/together-inference-vs-vertex-ai.json", "title": "Together AI Inference vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/together-inference-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/vercel-ai-gateway-vs-vertex-ai.json", "title": "Vercel AI Gateway vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/vercel-ai-gateway-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/vertex-ai-vs-xai-api.json", "title": "Vertex AI (Gemini Enterprise Agent Platform) vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/vertex-ai-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-cloudflare-ai-gateway.json", "title": "Antseed vs Cloudflare AI Gateway", "url": "https://www.anchorterminal.com/compare/antseed-vs-cloudflare-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-eden-ai.json", "title": "Antseed vs Eden AI", "url": "https://www.anchorterminal.com/compare/antseed-vs-eden-ai" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-hugging-face-inference-providers.json", "title": "Antseed vs Hugging Face Inference Providers", "url": "https://www.anchorterminal.com/compare/antseed-vs-hugging-face-inference-providers" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-litellm.json", "title": "Antseed vs LiteLLM", "url": "https://www.anchorterminal.com/compare/antseed-vs-litellm" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-openrouter.json", "title": "Antseed vs OpenRouter", "url": "https://www.anchorterminal.com/compare/antseed-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-ramp-router.json", "title": "Antseed vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/antseed-vs-ramp-router" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-routerplus.json", "title": "Antseed vs RouterPlus", "url": "https://www.anchorterminal.com/compare/antseed-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-tencent-tokenhub.json", "title": "Antseed vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/antseed-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-vercel-ai-gateway.json", "title": "Antseed vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/antseed-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-vertex-ai.json", "title": "Nemotron 3.5 Super VL vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-vertex-ai" } ], "panel": null, "scores": [ { "antseed": 52, "by": 47, "edge": "vertex-ai", "key": "reliability", "name": "Reliability", "vertex-ai": 99, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "antseed": 55, "by": 39, "edge": "vertex-ai", "key": "schema", "name": "Schema \u0026 documentation", "vertex-ai": 94, "weight": 13 }, { "antseed": 56, "by": 41, "edge": "vertex-ai", "key": "ergonomics", "name": "Agent ergonomics", "vertex-ai": 97, "weight": 13 }, { "antseed": 45, "by": 52, "edge": "vertex-ai", "key": "security", "name": "Security \u0026 auth", "vertex-ai": 97, "weight": 14 }, { "antseed": 70, "by": 30, "edge": "antseed", "key": "payments", "name": "Payments \u0026 pricing", "vertex-ai": 40, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "antseed": 79, "by": 12, "edge": "vertex-ai", "key": "maintenance", "name": "Maintenance \u0026 community", "vertex-ai": 91, "weight": 7 }, { "antseed": 59, "by": 31, "edge": "vertex-ai", "key": "transparency", "name": "Transparency \u0026 trust", "vertex-ai": 90, "weight": 7 } ], "summary": "Vertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against Antseed's 54.1 (C), and leads in 6 of 7 scored categories. Antseed leads on payments \u0026 pricing. Both do llm inference.", "tasks": null, "tutorials": [], "verdicts": { "antseed": "A buyer needs no account. The CLI creates a wallet key, free models answer at once and paid ones draw on deposited USDC, with seller, tokens and cost in response headers. Sellers are unvetted and can read prompts unless TEE-verified, the proxy forwarded client credentials to them until 12 October 2026 with no advisory, and every package is pre-1.0.", "vertex-ai": "Gemini, Claude and open models through one Google Cloud API with IAM, regional endpoints, schema-guaranteed JSON and a 99.5 per cent SLA, and no Vertex incident on the Cloud status page in the 90 days to 6 November 2026. Gemini 4 Argon and 3.8 Flash have 12-month availability, but short-term Flash models get a 95 per cent SLA." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/antseed-vs-vertex-ai", "json": "https://www.anchorterminal.com/compare/antseed-vs-vertex-ai.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/antseed-vs-vertex-ai.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/antseed-vs-vertex-ai.min.md" }, "markdown": "Vertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against Antseed's 54.1 (C), and leads in 6 of 7 scored categories. Antseed leads on payments \u0026 pricing. Both do llm inference.\n\n- Antseed: grade C, 54.1/100, rank #921 of 1510. Markdown https://www.anchorterminal.com/tools/antseed.md · JSON https://www.anchorterminal.com/api/v1/tools/antseed.json\n- Vertex AI (Gemini Enterprise Agent Platform): grade AA, 88.7/100, rank #2 of 1510. Markdown https://www.anchorterminal.com/tools/vertex-ai.md · JSON https://www.anchorterminal.com/api/v1/tools/vertex-ai.json\n- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md\n- All 830 models comparisons: https://www.anchorterminal.com/compare/inference/index.md\n\n## Which one, for what\n\n### Antseed (C)\n\nGood for: Agents and coding tools that want pay-per-request inference with no account, and owners comfortable holding USDC on Base.\n\nAhead on:\n- Payments \u0026 pricing, 70 against 40\n\nAlso in its favour:\n- No key needed to call it\n- Open source\n\nWatch for: The buyer proxy copied client credential headers to sellers until v0.2.58 (12 October 2026), with no published advisory\n\n### Vertex AI (Gemini Enterprise Agent Platform) (AA)\n\nGood for: Google Cloud customers who need Gemini with residency, VPC-SC, provisioned throughput and an SLA, or Claude under a Google bill.\n\nAhead on:\n- Reliability, 99 against 52\n- Schema \u0026 documentation, 94 against 55\n- Agent ergonomics, 97 against 56\n- Security \u0026 auth, 97 against 45\n- Maintenance \u0026 community, 91 against 79\n- Transparency \u0026 trust, 90 against 59\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n- A hosted endpoint, with nothing to install\n- No incidents deducted, where Antseed loses 3 points for them\n\nWatch for: The SLA drops from 99.5 to 95 per cent for short-term availability models, Gemini 3.7 and 3.6 Flash among them\n\n\n## Why the edge\n\n### Security \u0026 auth: Vertex AI (Gemini Enterprise Agent Platform) +52\n\n- Antseed (45): Model reading. The local proxy has no key and binds to 127.0.0.1. One secp256k1 key is identity and wallet, stored in plain text by the CLI unless supplied by environment variable, and encrypted by the OS keychain in the desktop app. Spending is bounded by a deposit contract, a capped ReserveAuth per seller and an optional separate withdrawal wallet, and gateway keys are hashed, revocable and spend-limited (18 of 30). Sellers are independent, and the FAQ says a standard seller can read prompts and sets its own practices (5 of 20). No central log, and an optional TEE-verified route with attestation checked on the buyer's machine (8 of 15). Seller, token and cost headers per response, `antseed buyer metering` and a Prometheus exporter (12 of 15). The buyer proxy stopped forwarding client credentials to sellers in v0.2.58 (12 October 2026). No SECURITY.md in the 4 November clone; no security.txt, published advisory, bug bounty, certification or contract audit report found. The repository holds one automated review of the buyer proxy dated 8 March 2026 (2 of 20). Docs per the 8 October check, not re-read on 4 November, because the terms of 9 October 2026 bar scripts that scrape or mine data from the Offerings, which include the documentation.\n- Vertex AI (Gemini Enterprise Agent Platform) (97): Model reading. OAuth 2.0 with IAM roles and service accounts, which the docs recommend for production, with API keys for testing. No key in a query string found in the docs we read (30). The training restriction in the Service Specific Terms says Google won't use customer data to train or fine-tune any model without permission, GA and pre-GA alike (20). Default in-memory caching for 24 hours that can be disabled, flagged prompts logged up to 90 days unless an abuse-monitoring exception is granted or the customer has a Cloud Master Agreement, the Interactions API storing by default, and Claude Fable 5 and Mythos 5 requiring 30-day retention shared with Anthropic (12 of 15, a judgement call matching the Fable exception on the Anthropic and Bedrock listings). Cloud Audit Logs, with Data Access logs off until enabled, and optional request-response logging to BigQuery (15). google.com security.txt valid to 2030-04-01, the Google VRP, and Generative AI on the platform in ISO 27001, 27017 and 27018 and SOC 1, 2 and 3 scope per the 1 October services-in-scope check for vertex-ai-tuning, not re-read on 6 October (20).\n\n### Reliability: Vertex AI (Gemini Enterprise Agent Platform) +47\n\n- Antseed (52): Read with the local-software lines, since the buyer runs the proxy. Official npm package @antseed/cli with Node.js 20 or later stated, plus desktop installers (20). Public CI on main runs the unit tests, an end-to-end suite and a payment flow (ci.yml in the clone), but the run results on GitHub couldn't be read on 4 November, so 15 of 25. Open issues and pull requests per the 8 October count (74 and 32), with bug reports from late September open then and reply times not sampled (12 of 25). CHANGELOG.md calls out breaking CLI changes, but versions are 0.x patch bumps and recent entries sit under one Unreleased heading (5 of 15). Release tag v0.2.72 and CLI 0.1.220 at that tag, with no statement of stability (0). Whether a request is answered also depends on which sellers are online, which this checklist doesn't score.\n- Vertex AI (Gemini Enterprise Agent Platform) (99): Google Cloud status dashboard with per-product history (20). Its incident feed, read on 6 November, has no incident naming Vertex Gemini API, Gemini or the Agent Platform in the 90 days. The regional incidents of 20 August, 1 September and 20 October (europe-west2) and the Cloud Storage incident of 8 and 9 October didn't list it among affected products (30). Standard PayGo publishes usage tiers by 30-day spend with baseline throughput, 2,000,000 to 50,000,000 tokens a minute for Flash models and 500,000 to 10,000,000 for Pro, plus quota tables for other methods (15). A 429 page says to use the global endpoint and truncated exponential backoff, and a retry-strategy page (15). SLA of 99.5 per cent a month on generateContent and streamGenerateContent, 95 per cent for short-term availability models, and a latency SLO on Provisioned Throughput. The 429 page says pay-as-you-go 429s don't count toward the SLA error rate (10). Gemini 4 Argon reached GA on 13 October and Gemini 3.8 Flash moved to the 12-month tier, and the v1 API, 3.5 Flash-Lite and Claude Opus 5.5 are GA, but express mode was Preview at the 6 October check (9 of 10, up from 8). Up from 98 on 6 October.\n\n### Agent ergonomics: Vertex AI (Gemini Enterprise Agent Platform) +41\n\n- Antseed (56): Model reading, as for other routers. Tool use and structured output depend on the seller, and the model list reports both per seller with conservative model-level values (12 of 20 and 8 of 15). Cached-input pricing is advertised per seller where supported (8 of 15). Context length is reported per model as the lowest value across sellers (10 of 15). No batch route found (0 of 10). No SDK of its own for buyers. OpenAI and Anthropic SDKs work against the proxy, and wrappers launch Claude Code, Codex and OpenCode (5 of 10). Documented error codes with fixes, and cost and seller headers on non-streaming responses (13 of 15). Docs per the 8 October check, not re-read on 4 November, because the terms of 9 October 2026 bar scripts that scrape or mine data from the Offerings, which include the documentation.\n- Vertex AI (Gemini Enterprise Agent Platform) (97): Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Function calling with `FunctionCallingConfig` mode ANY and `allowedFunctionNames` to force a named tool (20). Schema-guaranteed JSON output (15). Implicit and explicit context caching, cached input at 0.1x, $0.075 per million on 3.8 Flash through 31 December (15). 1,048,576-token context on 3.8 Flash, a unified 1,048,576-token input and output limit on Gemini 4 Argon, and 1,000,000 on Claude Opus 5.5 (15). Flex/Batch at half price on Gemini (10). Gen AI SDKs for Python and JavaScript among others, and the OpenAI libraries work with Google Cloud auth (10). 429 handling documented per quota framework, with standard Google status codes elsewhere (12 of 15).\n\n### Schema \u0026 documentation: Vertex AI (Gemini Enterprise Agent Platform) +39\n\n- Antseed (55): No OpenAPI document found in the repository or docs. The proxy copies the OpenAI and Anthropic wire formats (0 of 25). llms.txt at antseed.com/llms.txt and a setup skill at /skill.md (10). The API guide states what each route is for, how routing picks a seller and when to pin one (14 of 20). Request bodies follow the upstream formats, and `/v1/models` reports context length, modalities, tool use and supported parameters per seller (8 of 15). Curl examples for each format and an error table with status, code, meaning and fix (13 of 15). A public changelog and tagged releases, with recent entries under an undated Unreleased heading (10 of 15). Docs per the 8 October check, not re-read on 4 November, because the terms of 9 October 2026 bar scripts that scrape or mine data from the Offerings, which include the documentation.\n- Vertex AI (Gemini Enterprise Agent Platform) (94): Model reading. Keyless discovery document for the Agent Platform API v1, revision 20260930, with 1,128 methods and 1,493 schemas (25). No llms.txt, but every docs page answers as Markdown at `.md.txt`, counted as for vertex-ai-tuning (10). Model cards give limits, capabilities and retirement dates, and the 3.8 Flash card says when to use 3.7 Flash instead, but the docs mix the Vertex AI and Agent Platform names, and the OpenAI page tells new users to call the Gemini Developer API instead (16 of 20). Structured output with `response_schema` and `response_mime_type: application/json` always follows the schema per the docs, and complex schemas fail with a 400 (15). Examples on every page and a 429 guide, but we found no full error code list for generateContent (13 of 15). Versioned v1 and v1beta1 APIs and release notes with entries on most working days, newest 5 November 2026 (15).\n\n### Transparency \u0026 trust: Vertex AI (Gemini Enterprise Agent Platform) +31\n\n- Antseed (59): GPL-3.0 source for the protocol, CLI, desktop app and contracts (30). The terms (last updated 9 October 2026), FAQ and privacy page agree that there is no central request log and that sellers may log prompts. There is no privacy policy document, and docs/telemetry.md says the PostHog region and retention period are still to be documented (12 of 30). No deprecation policy found. The changelog gives version cut-offs for protocol changes and a dated cutover of 10 September 2026 for staking contracts (8 of 20). Desktop telemetry is documented event by event with a toggle and an environment switch, and is keyed to the buyer's public wallet address. No telemetry code found in the CLI (16 of 20). docs/telemetry.md is unchanged since 15 September 2026 in the 4 November clone.\n- Vertex AI (Gemini Enterprise Agent Platform) (90): Closed service under the Google Cloud terms, with the Gen AI SDKs under Apache-2.0 and a public discovery document (18, as for Bedrock's open service models). The zero data retention and abuse monitoring pages agree with the Cloud terms and give periods for each case, 24 hours in memory, up to 90 days for flagged prompts, 30 days for Advanced AI models, 3 days for Search grounding logs and 30 days for Maps grounding, and say which can't be switched off (27 of 30). A dated model versions table with release and retirement dates and a stated 12-month or 45-day policy, but on 6 November it still listed Gemini 2.5 Pro, Flash and Flash-Lite as available with a 20 October 2026 retirement date and left them out of the retired table (18 of 20, down from 20). The Cloud subprocessor list with locations, per the 1 October vertex-ai-tuning check, regional and multi-region endpoints, and per-model ML processing locations on the partner model cards (20).\n\n### Payments \u0026 pricing: Antseed +30\n\n- Antseed (70): x402 v2 exists only on `POST /v1/key/topup` of a gateway the owner runs, and is off until enabled per key. Inference is paid through Antseed's own HTTP 402 flow with EIP-712 signatures and USDC channels on Base, which isn't one of the three protocols the rubric names (10 of 40, a judgement call). PRICING.md in the repository says seller prices per 1M tokens are published without authentication at a cached endpoint and live through `antseed network browse --json` (20); the 8 October snapshot figures came from that JSON endpoint and are struck. Free models answer with no card and no account, per the docs on 8 October (20). An agent can install the CLI, get a key generated locally and fund it by a USDC transfer, with no sign-up flow (20). The self-hosted rule gives the same three lines for the free software.\n- Vertex AI (Gemini Enterprise Agent Platform) (40): No x402, MPP or L402 (0). Per-token prices per model and option published without a login (20). Express mode gives new Google Cloud users 90 days free within quotas with no billing details, though it's in Preview and needs a @gmail.com account (20). A person signs up in the console to get the express key (0).\n\n## Score by category\n\n| Category | Weight | Antseed | Vertex AI (Gemini Enterprise Agent Platform) | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 52 | 99 | Vertex AI (Gemini Enterprise Agent Platform) +47 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 55 | 94 | Vertex AI (Gemini Enterprise Agent Platform) +39 |\n| Agent ergonomics | 13% (16.2 this run) | 56 | 97 | Vertex AI (Gemini Enterprise Agent Platform) +41 |\n| Security \u0026 auth | 14% (17.5 this run) | 45 | 97 | Vertex AI (Gemini Enterprise Agent Platform) +52 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 70 | 40 | Antseed +30 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 79 | 91 | Vertex AI (Gemini Enterprise Agent Platform) +12 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 59 | 90 | Vertex AI (Gemini Enterprise Agent Platform) +31 |\n| Negative events | ≤15 | -3 | 0 | |\n| **Total** | | **54.1 · C** | **88.7 · AA** | |\n\n## Facts side by side\n\n| Fact | Antseed | Vertex AI (Gemini Enterprise Agent Platform) |\n| --- | --- | --- |\n| Kind | Model router | Model API |\n| Vendor | Antseed Foundation | Google Cloud |\n| Hosted endpoint | no (local only) | `https://aiplatform.googleapis.com/v1` |\n| Transports | HTTP | HTTP |\n| Auth | None | OAuth or key |\n| Pricing | Pay per use | Pay per use |\n| x402 | no | no |\n| Licence | GPL-3.0 (LICENSE in the repository). The @antseed/cli manifest on npm carries no licence field | Proprietary service under the Google Cloud Platform terms. Partner models carry their providers' terms. The Google Gen AI SDKs are Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | no |\n| Last release | 2026-10-31 | 2026-11-05 |\n| Terms last updated | 2026-05-15 | 2026-09-02 |\n| Privacy policy last updated | no document linked | 2026-10-01 |\n| Customer content may train models | not found in the text | yes |\n| Terms restrict automated access | not found in the text | not found in the text |\n| Terms restrict benchmarking | not found in the text | not found in the text |\n| Terms or service can change without notice | not found in the text | not found in the text |\n| Arbitration or class-action waiver | not found in the text | not found in the text |\n| Popularity | 106 stars, 1.8k npm/wk | 20.9M PyPI/wk |\n\n## How the scores have moved\n\n### Antseed\n\n- -1.0 on 4 November 2026: security, new evidence\n\n### Vertex AI (Gemini Enterprise Agent Platform)\n\nNo score change since it was listed.\n\n## Verdicts\n\n**Antseed.** A buyer needs no account. The CLI creates a wallet key, free models answer at once and paid ones draw on deposited USDC, with seller, tokens and cost in response headers. Sellers are unvetted and can read prompts unless TEE-verified, the proxy forwarded client credentials to them until 12 October 2026 with no advisory, and every package is pre-1.0.\n\n**Vertex AI (Gemini Enterprise Agent Platform).** Gemini, Claude and open models through one Google Cloud API with IAM, regional endpoints, schema-guaranteed JSON and a 99.5 per cent SLA, and no Vertex incident on the Cloud status page in the 90 days to 6 November 2026. Gemini 4 Argon and 3.8 Flash have 12-month availability, but short-term Flash models get a 95 per cent SLA.\n\n## Before you call either\n\n### Antseed\n\n1. Send a placeholder key such as `antseed-p2p`, and run v0.2.58 or later, which stops credential headers reaching sellers.\n2. Call `GET /v1/models` first and request a concrete id. The `antseed` alias works only when the desktop app has a model selected\n3. Handle 402 `insufficient_deposits` by reading `suggestedAmount`, then fund the address from `antseed buyer deposit` with USDC on Base\n4. Pass `--verifiers antseed-verifier --require-verifier` to `antseed buyer start` when prompts are private, so only TEE-verified sellers are routed\n5. Read `x-antseed-peer-id` and `x-antseed-estimated-cost-usd` on each response, and pin a seller with `\u003cpeerId\u003e@\u003cmodel\u003e` when the same one must answer\n\n### Vertex AI (Gemini Enterprise Agent Platform)\n\n1. Call the `global` location on aiplatform.googleapis.com unless data residency requires a Region. The 429 guide says it spreads load and reduces errors\n2. Back off exponentially on 429 `Resource exhausted`. On Standard PayGo it means shared capacity is busy, not a fixed quota\n3. Send `response_schema` with `response_mime_type: application/json`. JSON mode alone doesn't guarantee valid output\n4. Set `store` to false on Interactions API calls. It defaults to true and keeps prompts and responses\n5. Pin `gemini-4-argon` or `gemini-3.8-flash`, both in the 12-month tier, rather than 3.7 or 3.6 Flash, which retire on 28 January 2027 and 19 November 2026\n\n## Questions\n\n### Which is better for AI agents, Antseed or Vertex AI (Gemini Enterprise Agent Platform)?\n\nVertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against Antseed's 54.1 (C), and leads in 6 of 7 scored categories. Antseed leads on payments \u0026 pricing.\n\n### Do Antseed and Vertex AI (Gemini Enterprise Agent Platform) need an API key?\n\nAntseed needs no key. Vertex AI (Gemini Enterprise Agent Platform) takes an API key or an OAuth sign-in.\n\n### Can an agent call Antseed and Vertex AI (Gemini Enterprise Agent Platform) without installing anything?\n\nNo hosted endpoint is listed for Antseed. Vertex AI (Gemini Enterprise Agent Platform) has a hosted endpoint at https://aiplatform.googleapis.com/v1.\n\n### Are Antseed and Vertex AI (Gemini Enterprise Agent Platform) open source?\n\nAntseed is open source (GPL-3.0 (LICENSE in the repository). The @antseed/cli manifest on npm carries no licence field). No open-source release is listed for Vertex AI (Gemini Enterprise Agent Platform).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/antseed-vs-vertex-ai.json, and with the fewest tokens: https://www.anchorterminal.com/compare/antseed-vs-vertex-ai.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"antseed\", \"b\": \"vertex-ai\"}`. From a terminal: `anchor compare antseed vertex-ai`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/antseed.json and https://www.anchorterminal.com/api/v1/tools/vertex-ai.json\n\n## Other comparisons with Antseed or Vertex AI (Gemini Enterprise Agent Platform)\n\n- [Amazon Bedrock vs Antseed](https://www.anchorterminal.com/compare/amazon-bedrock-vs-antseed.md)\n- [Amazon Bedrock vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/amazon-bedrock-vs-vertex-ai.md)\n- [Claude API vs Antseed](https://www.anchorterminal.com/compare/anthropic-api-vs-antseed.md)\n- [Claude API vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/anthropic-api-vs-vertex-ai.md)\n- [Antseed vs Azure OpenAI in Foundry Models](https://www.anchorterminal.com/compare/antseed-vs-azure-openai.md)\n- [Antseed vs BlockRun.AI](https://www.anchorterminal.com/compare/antseed-vs-blockrun-ai.md)\n- [Antseed vs Cerebras Inference](https://www.anchorterminal.com/compare/antseed-vs-cerebras-inference.md)\n- [Antseed vs Cloudflare Workers AI](https://www.anchorterminal.com/compare/antseed-vs-cloudflare-workers-ai.md)\n- [Antseed vs Cohere Chat API (Command models)](https://www.anchorterminal.com/compare/antseed-vs-cohere-chat.md)\n- [Antseed vs DeepInfra](https://www.anchorterminal.com/compare/antseed-vs-deepinfra.md)\n- [Antseed vs DeepSeek API](https://www.anchorterminal.com/compare/antseed-vs-deepseek-api.md)\n- [Antseed vs Glimpse](https://www.anchorterminal.com/compare/antseed-vs-elorian-glimpse.md)\n- [Antseed vs Fireworks AI Inference](https://www.anchorterminal.com/compare/antseed-vs-fireworks-inference.md)\n- [Antseed vs Gemini Developer API](https://www.anchorterminal.com/compare/antseed-vs-gemini-api.md)\n- [Antseed vs GroqCloud](https://www.anchorterminal.com/compare/antseed-vs-groq.md)\n- [Antseed vs Inkling 2 Small](https://www.anchorterminal.com/compare/antseed-vs-inkling-2-small.md)\n- [Antseed vs Jais 3](https://www.anchorterminal.com/compare/antseed-vs-jais-3.md)\n- [Antseed vs Meta Model API](https://www.anchorterminal.com/compare/antseed-vs-meta-model-api.md)\n- [Antseed vs MiniMax API](https://www.anchorterminal.com/compare/antseed-vs-minimax-api.md)\n- [Antseed vs Mistral AI API](https://www.anchorterminal.com/compare/antseed-vs-mistral-api.md)\n- [Antseed vs Muse Spark Open](https://www.anchorterminal.com/compare/antseed-vs-muse-spark-open.md)\n- [Antseed vs Nemotron 3.5 Super VL](https://www.anchorterminal.com/compare/antseed-vs-nemotron-3-5-super-vl.md)\n- [Antseed vs Novita AI](https://www.anchorterminal.com/compare/antseed-vs-novita-ai.md)\n- [Antseed vs OpenAI API](https://www.anchorterminal.com/compare/antseed-vs-openai-api.md)\n- [Antseed vs Prism Inference](https://www.anchorterminal.com/compare/antseed-vs-prism-inference.md)\n- [Antseed vs Beam 1.0](https://www.anchorterminal.com/compare/antseed-vs-reflection-beam.md)\n- [Antseed vs SambaCloud](https://www.anchorterminal.com/compare/antseed-vs-sambanova.md)\n- [Antseed vs SiliconFlow](https://www.anchorterminal.com/compare/antseed-vs-siliconflow.md)\n- [Antseed vs Simplismart](https://www.anchorterminal.com/compare/antseed-vs-simplismart.md)\n- [Antseed vs StepFun API](https://www.anchorterminal.com/compare/antseed-vs-stepfun-api.md)\n- [Antseed vs SWE-2 Flash](https://www.anchorterminal.com/compare/antseed-vs-swe-2-flash.md)\n- [Antseed vs Together AI Inference](https://www.anchorterminal.com/compare/antseed-vs-together-inference.md)\n- [Antseed vs xAI API (Grok)](https://www.anchorterminal.com/compare/antseed-vs-xai-api.md)\n- [Azure OpenAI in Foundry Models vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/azure-openai-vs-vertex-ai.md)\n- [BlockRun.AI vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/blockrun-ai-vs-vertex-ai.md)\n- [Cerebras Inference vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/cerebras-inference-vs-vertex-ai.md)\n- [Cloudflare AI Gateway vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-vertex-ai.md)\n- [Cloudflare Workers AI vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-vertex-ai.md)\n- [Cohere Chat API (Command models) vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/cohere-chat-vs-vertex-ai.md)\n- [DeepInfra vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/deepinfra-vs-vertex-ai.md)\n- [DeepSeek API vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/deepseek-api-vs-vertex-ai.md)\n- [Eden AI vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/eden-ai-vs-vertex-ai.md)\n- [Glimpse vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/elorian-glimpse-vs-vertex-ai.md)\n- [Fireworks AI Inference vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/fireworks-inference-vs-vertex-ai.md)\n- [Gemini Developer API vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/gemini-api-vs-vertex-ai.md)\n- [GroqCloud vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/groq-vs-vertex-ai.md)\n- [Hugging Face Inference Providers vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vertex-ai.md)\n- [Inkling 2 Small vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/inkling-2-small-vs-vertex-ai.md)\n- [Jais 3 vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/jais-3-vs-vertex-ai.md)\n- [Meta Model API vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/meta-model-api-vs-vertex-ai.md)\n- [MiniMax API vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/minimax-api-vs-vertex-ai.md)\n- [Mistral AI API vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/mistral-api-vs-vertex-ai.md)\n- [Muse Spark Open vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/muse-spark-open-vs-vertex-ai.md)\n- [Novita AI vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/novita-ai-vs-vertex-ai.md)\n- [OpenAI API vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/openai-api-vs-vertex-ai.md)\n- [OpenRouter vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/openrouter-vs-vertex-ai.md)\n- [Prism Inference vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/prism-inference-vs-vertex-ai.md)\n- [Router.com (Ramp Router) vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/ramp-router-vs-vertex-ai.md)\n- [Beam 1.0 vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/reflection-beam-vs-vertex-ai.md)\n- [RouterPlus vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/routerplus-vs-vertex-ai.md)\n- [SambaCloud vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/sambanova-vs-vertex-ai.md)\n- [SiliconFlow vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/siliconflow-vs-vertex-ai.md)\n- [Simplismart vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/simplismart-vs-vertex-ai.md)\n- [StepFun API vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/stepfun-api-vs-vertex-ai.md)\n- [SWE-2 Flash vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/swe-2-flash-vs-vertex-ai.md)\n- [Tencent Cloud TokenHub vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/tencent-tokenhub-vs-vertex-ai.md)\n- [Together AI Inference vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/together-inference-vs-vertex-ai.md)\n- [Vercel AI Gateway vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/vercel-ai-gateway-vs-vertex-ai.md)\n- [Vertex AI (Gemini Enterprise Agent Platform) vs xAI API (Grok)](https://www.anchorterminal.com/compare/vertex-ai-vs-xai-api.md)\n- [Antseed vs Cloudflare AI Gateway](https://www.anchorterminal.com/compare/antseed-vs-cloudflare-ai-gateway.md)\n- [Antseed vs Eden AI](https://www.anchorterminal.com/compare/antseed-vs-eden-ai.md)\n- [Antseed vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/antseed-vs-hugging-face-inference-providers.md)\n- [Antseed vs LiteLLM](https://www.anchorterminal.com/compare/antseed-vs-litellm.md)\n- [Antseed vs OpenRouter](https://www.anchorterminal.com/compare/antseed-vs-openrouter.md)\n- [Antseed vs Router.com (Ramp Router)](https://www.anchorterminal.com/compare/antseed-vs-ramp-router.md)\n- [Antseed vs RouterPlus](https://www.anchorterminal.com/compare/antseed-vs-routerplus.md)\n- [Antseed vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/antseed-vs-tencent-tokenhub.md)\n- [Antseed vs Vercel AI Gateway](https://www.anchorterminal.com/compare/antseed-vs-vercel-ai-gateway.md)\n- [Nemotron 3.5 Super VL vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-vertex-ai.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-11-07", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.7", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Antseed vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "" } ], "description": "Vertex AI scores 88.7 (AA) to Antseed's 54.1 (C) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Antseed C 54.1", "Vertex AI (Gemini Enterprise Agent Platform) AA 88.7", "scores" ], "h1": "Antseed vs Vertex AI (Gemini Enterprise Agent Platform)", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/antseed-vs-vertex-ai", "published": "2026-10-01", "section": "tools", "title": "Antseed vs Vertex AI for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-11-07", "url": "https://www.anchorterminal.com/compare/antseed-vs-vertex-ai" }, "tokens": { "markdown": 7450, "slim": 3580 }, "version": 1 }