{ "data": { "a": { "slug": "vercel-ai-gateway", "name": "Vercel AI Gateway", "vendor": "Vercel Inc.", "vendorUrl": "https://vercel.com", "kind": "router", "category": "inference", "summary": "Vercel AI Gateway is a hosted router for model APIs. One API key or Vercel OIDC token reaches models from OpenAI, Anthropic, Google and others through OpenAI-compatible, Anthropic-compatible and AI SDK interfaces, with budgets, request logs and provider failover.", "url": "https://www.anchorterminal.com/tools/vercel-ai-gateway", "markdownUrl": "https://www.anchorterminal.com/tools/vercel-ai-gateway.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/vercel-ai-gateway.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/vercel-ai-gateway.json", "dns": "vercel-ai-gateway.grade.anchorterminal.com", "repo": "https://github.com/vercel/ai", "license": "Proprietary service under Vercel's Terms of Service and AI Product Terms, with Token Pass terms on its docs page. Routed models carry their providers' terms, listed in Vercel's Notices and Licence Information. The `@ai-sdk/gateway` provider is Apache-2.0", "transports": [ "http" ], "remoteUrl": "https://ai-gateway.vercel.sh/v1", "packages": [ { "registry": "npm", "name": "@ai-sdk/gateway" }, { "registry": "npm", "name": "ai" }, { "registry": "pypi", "name": "ai" } ], "auth": "mixed", "authNotes": "An AI Gateway API key as a Bearer token from any environment, or a Vercel OIDC token on Vercel deployments (12 hours locally, refreshed with `vercel env pull`). Keys belong to a team, can be limited to one project and given an expiry and a budget, and are created in the dashboard, with the Vercel CLI or by `POST /v1/api-keys` with a Vercel access token. A person creates the Vercel account in a browser. Token Pass needs its own Token Pass API key, and OIDC tokens cannot spend Token Pass credit.", "pricing": "usage", "pricingNotes": "Prepaid AI Gateway Credits at each provider's list price, with no markup or platform fee, including BYOK. A monthly free credit covers a subset of models and needs a valid payment method on the team. Credits expire a year after purchase. Add-ons are billed separately, and Token Pass is $30 a team a month on Pro for $80 of credit on two models, in early access (https://vercel.com/docs/ai-gateway/pricing, https://vercel.com/docs/ai-gateway/token-pass, checked 2026-10-17).", "priceSummary": "$30 / mo", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the AI Gateway docs, the pricing page, the Token Pass pages or the AI Gateway entries of the changelog sitemap. Payment is by prepaid credits bought with a card, or by invoice on Enterprise (checked 2026-10-17).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": 29597661, "pypiWeekly": null, "asOf": "2026-10-17" }, "docsUrl": "https://vercel.com/docs/ai-gateway", "llmsTxt": "https://vercel.com/llms.txt", "openapi": "https://vercel.com/openapi.json", "capabilities": [ "inference.router", "inference.llm", "inference.fast", "inference.decision", "obs.gateway", "obs.traces", "embed.text", "image.generate", "video.generate" ], "tags": [ "hosted", "router", "usage-based", "prepaid", "free-tier", "openai-compatible", "anthropic-compatible", "llms-txt", "openapi", "typescript", "python", "oidc", "cli", "early-access", "status-page", "bug-bounty", "soc2", "iso27001" ], "lastRelease": "2026-10-30", "graded": true, "anchor": { "graded": true, "score": 67.8, "grade": "B", "agentReady": false, "rank": 302, "ranked": true, "rankOf": 1486, "categoryRank": 14, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 83, "maintenance": 79, "payments": 20, "reliability": 79, "schema": 74, "security": 79, "transparency": 71 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-01" }, "negative": -3, "negativeNotes": [ "April 2026. Vercel's security bulletin says an attacker took over an employee's account through a compromised third-party AI tool, reached internal systems and decrypted non-sensitive environment variables of a limited subset of customers. AI Gateway was generally available then, and its docs have deployments keep AI Gateway and Token Pass API keys as environment variables. The bulletin documents remediation and marks the incident closed on 16 October 2026, so 3 of a possible 15 is taken, as for vercel-connect (https://vercel.com/kb/bulletin/vercel-april-2026-security-incident)." ], "verdict": "Token prices pass through with no markup, prompts are not stored by the gateway, and budgets, provider failover and per-request logs are built in. The free monthly credit needs a card on file, rate limits are not published as numbers, no SLA covers the API, and the contractual promise not to train on content applies to Enterprise subscriptions only.", "bestFor": "Teams that want one key, one bill, budgets and failover in front of many model providers, especially on Vercel with OIDC.", "strengths": [ "Token prices are each provider's list price with no markup or platform fee, including requests made with the customer's own provider keys", "The model list at `GET /v1/models` needs no key and gives prices, context windows, supported parameters and ZDR and no-training flags for 498 models", "Budgets per team, project, API key or team member reject spend with a 402, distinct from a 429 rate limit", "The gateway logs request metadata only. Prompt and response content is deleted when the request completes, per the FAQ and the ZDR page", "Failed provider attempts are retried on a model's other providers, and every routing attempt appears in the request logs" ], "weaknesses": [ "The free monthly credit needs a valid payment method on the team, and its amount is not stated in the reviewed docs", "No rate-limit numbers are published, and the Enterprise SLA excludes the APIs, so the inference API carries no uptime commitment", "The contractual promise not to train on AI Gateway content covers Enterprise subscriptions only. Provider no-training and ZDR filters are opt-in per request", "A failed BYOK request falls back to Vercel's credentials and is billed to credits, and the no-training filter is not applied to BYOK", "Token Pass is early access for Pro teams only, covers two models, has no failover and fails with a 403 once the $80 credit is spent" ], "agentNotes": [ "Read `GET https://ai-gateway.vercel.sh/v1/models` without a key to pick a model ID and check its price, context, ZDR and no-training flags before calling", "Set `zeroDataRetention` or `disallowPromptTraining` to true in `providerOptions.gateway` on sensitive requests. Default routing ignores provider retention and training policies", "Treat a 429 as retryable and honour `retry-after` when present. A 402 with `quota_for_entity_exceeded` is a spent budget, so do not retry it", "On a Token Pass key, a 403 with `no_providers_available` means spent credit or a model outside the pass. Retry with a standard AI Gateway key, which bills credits", "Set `inferenceRegion` when data residency matters. The default `global` may run inference outside the user's jurisdiction" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 4, "avgRating": 3, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 67.8 } ], "editorialScores": { "ergonomics": 83, "maintenance": 79, "payments": 20, "reliability": 79, "schema": 74, "security": 79, "transparency": 55 }, "provenanceScore": 86, "checked": { "categories": { "ergonomics": "2026-11-01", "maintenance": "2026-11-01", "payments": "2026-11-01", "reliability": "2026-11-01", "schema": "2026-11-01", "security": "2026-11-01", "transparency": "2026-11-01" }, "last": "2026-11-01", "lastMoved": "2026-11-01", "oldest": "2026-11-01", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pnpm add ai@latest", "http": "curl https://ai-gateway.vercel.sh/v1/chat/completions \\\n -H \"Authorization: Bearer $AI_GATEWAY_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"model\": \"openai/gpt-6-astra\",\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Explain AI Gateway in one sentence.\"\n }\n ]\n }'" }, "letme": { "capability": "https://letme.dev/inference.router", "tool": "https://letme.dev/vercel-ai-gateway" }, "sameCompany": [ "vercel-sandbox", "vercel-connect" ], "area": "models", "unitPrices": [ { "item": "Token Pass subscription (Pro teams)", "unit": "month", "usd": 30, "note": "$80 of monthly credit on two featured models. Early access" }, { "item": "Team-wide Zero Data Retention", "unit": "1k-requests", "usd": 0.1, "note": "Pro and Enterprise. Per-request ZDR is free" }, { "item": "Team-wide provider allowlist", "unit": "1k-requests", "usd": 0.1, "note": "Successful requests, Pro and Enterprise" }, { "item": "Custom Reporting query", "unit": "1k-requests", "usd": 5, "note": "Queries to the reporting endpoint" }, { "item": "Custom Reporting write of a tag, user ID or quota entity ID", "unit": "1k-requests", "usd": 0.075, "note": "Each unique value in a request counts as one write" }, { "item": "AI Gateway trace delivered to a drain", "unit": "1k-requests", "usd": 0.05, "note": "Listed per 1,000 traces, Pro and Enterprise" }, { "item": "Trace egress", "unit": "gb", "usd": 0.5, "note": "Billed through Drains usage" } ], "provenance": { "legalEntity": "Vercel Inc.", "domain": "vercel.com", "domainRegistered": "1999-10-04", "endpointOnVendorDomain": false, "terms": "https://vercel.com/legal/terms", "privacy": "https://vercel.com/legal/privacy-policy", "statusPage": "https://www.vercel-status.com", "changelog": "https://vercel.com/changelog", "securityTxt": "valid", "checked": "2026-11-01", "notes": [ "The Terms of Service (last updated 19 October 2026) name Vercel Inc. The AI Product Terms (last updated 17 March 2026, effective 31 March 2026) have a section for AI Gateway and form part of those terms.", "The Privacy Notice is effective from 1 June 2026. The DPA (effective 31 March 2026) applies to Pro and Enterprise plans.", "https://vercel.com/.well-known/security.txt points to HackerOne and responsible.disclosure@vercel.com and expires 2027-09-28 (re-read 1 November 2026).", "The API answers at ai-gateway.vercel.sh, a Vercel domain other than vercel.com. Management calls go to api.vercel.com.", "RDAP gives vercel.com a registration date of 1999-10-04, long before Vercel, so the domain was bought later.", "AI Gateway is a component on the status page at www.vercel-status.com." ], "score": 86 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/vercel-ai-gateway.json", "live": { "slug": "vercel-ai-gateway", "probe": { "target": "https://ai-gateway.vercel.sh/v1", "method": "get", "lastAt": "2026-11-07T18:21:03.439719131Z", "lastOk": true, "lastStatus": 404, "lastMs": 135, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 41, "p95ms24h": 147, "samples24h": 239, "samples30d": 5145, "days": [ { "date": "2026-10-17", "probes": 21, "ok": 21 }, { "date": "2026-10-18", "probes": 256, "ok": 256 }, { "date": "2026-10-19", "probes": 255, "ok": 255 }, { "date": "2026-10-20", "probes": 252, "ok": 252 }, { "date": "2026-10-21", "probes": 253, "ok": 253 }, { "date": "2026-10-22", "probes": 253, "ok": 253 }, { "date": "2026-10-23", "probes": 248, "ok": 248 }, { "date": "2026-10-24", "probes": 251, "ok": 251 }, { "date": "2026-10-25", "probes": 250, "ok": 250 }, { "date": "2026-10-26", "probes": 252, "ok": 252 }, { "date": "2026-10-27", "probes": 249, "ok": 249 }, { "date": "2026-10-28", "probes": 250, "ok": 250 }, { "date": "2026-10-29", "probes": 249, "ok": 249 }, { "date": "2026-10-30", "probes": 249, "ok": 249 }, { "date": "2026-10-31", "probes": 251, "ok": 251 }, { "date": "2026-11-01", "probes": 249, "ok": 249 }, { "date": "2026-11-02", "probes": 250, "ok": 250 }, { "date": "2026-11-03", "probes": 248, "ok": 248 }, { "date": "2026-11-04", "probes": 246, "ok": 246 }, { "date": "2026-11-05", "probes": 185, "ok": 185 }, { "date": "2026-11-06", "probes": 241, "ok": 241 }, { "date": "2026-11-07", "probes": 187, "ok": 187 } ] }, "vendorStatus": { "page": "https://www.vercel-status.com", "indicator": "none", "summary": "All Systems Operational", "checkedAt": "2026-11-07T18:22:06.975781508Z" }, "versions": [ { "registry": "github", "name": "vercel/ai", "version": "@ai-sdk/zai@2.0.19", "released": "2026-11-06", "seenAt": "2026-11-07T00:14:59.873146448Z" }, { "registry": "npm", "name": "@ai-sdk/gateway", "version": "4.0.137", "seenAt": "2026-11-07T00:14:55.531229295Z" }, { "registry": "npm", "name": "ai", "version": "7.0.164", "seenAt": "2026-11-07T00:14:55.80980887Z" }, { "registry": "pypi", "name": "ai", "version": "0.9.0", "released": "2026-11-04", "seenAt": "2026-11-07T00:14:57.789982799Z" } ], "githubStars": 27784, "npmWeekly": 43526403, "pypiWeekly": 30345, "securityTxt": { "url": "https://vercel.com/.well-known/security.txt", "state": "valid", "expires": "2027-09-28T12:00:00.000Z", "checkedAt": "2026-11-07T16:01:04.63743298Z" }, "llmsTxt": { "url": "https://vercel.com/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:34:15.91494374Z" }, "domain": { "domain": "vercel.com", "registered": "1999-10-04", "source": "https://rdap.verisign.com/com/v1/domain/vercel.com", "checkedAt": "2026-11-01T14:26:56.031194695Z" }, "pages": [ { "url": "https://vercel.com/changelog", "kind": "changelog", "status": 200, "checkedAt": "2026-11-07T14:23:18.843079137Z", "changedAt": "2026-11-07T14:23:18.843079137Z", "fingerprint": "87cda10f5c5b" }, { "url": "https://ai-gateway.vercel.sh/v1/models", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-07T13:58:54.859281938Z", "changedAt": "0001-01-01T00:00:00Z" }, { "url": "https://vercel.com/changelog/laya-decision-model-now-available-on-ai-gateway-free-through-october-31", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-07T14:23:21.044064491Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "6bbbff189272" }, { "url": "https://vercel.com/changelog/tako-search-is-free-on-ai-gateway-through-september-30th", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-07T14:23:23.299815086Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "196bc432bb9c" }, { "url": "https://vercel.com/docs/ai-gateway/pricing", "kind": "pricing", "status": 200, "checkedAt": "2026-11-07T14:23:25.343283135Z", "changedAt": "2026-11-06T13:44:45.951689623Z", "fingerprint": "6635a49dd249" }, { "url": "https://vercel.com/legal/privacy-policy", "kind": "privacy", "status": 200, "checkedAt": "2026-11-07T14:23:31.093414072Z", "changedAt": "2026-10-28T04:46:11.674155692Z", "fingerprint": "c545eb853c20" }, { "url": "https://vercel.com/legal/terms", "kind": "terms", "status": 200, "checkedAt": "2026-11-07T14:23:33.273454306Z", "changedAt": "2026-10-28T04:46:13.475126487Z", "fingerprint": "100a29fa0aba" } ], "github": { "repo": "vercel/ai", "checkedAt": "2026-11-02T09:35:36.328615652Z", "stars": 27693, "archived": false, "issuesEnabled": true, "pushedAt": "2026-11-02T09:18:34Z", "openIssues": 505, "openPRs": 1043, "issuesOpened90d": 1077, "issuesClosed90d": 1415, "prsMerged90d": 2573, "ci": { "branch": "main", "runs": 50, "success": 48, "failure": 2, "other": 0, "latest": "success", "latestAt": "2026-11-02T05:34:51Z" }, "advisories": [ { "ghsa": "GHSA-g3x3-7q3h-gmhj", "severity": "medium", "published": "2026-10-01T19:22:11Z" }, { "ghsa": "GHSA-4mqq-99j3-3hmv", "severity": "high", "published": "2026-09-28T17:44:55Z" }, { "ghsa": "GHSA-222v-gj5h-ff73", "severity": "high", "published": "2026-08-20T21:21:04Z" }, { "ghsa": "GHSA-vmqp-7rwf-cq3w", "severity": "medium", "published": "2026-08-14T01:39:36Z" }, { "ghsa": "GHSA-qw9h-448j-6rph", "cve": "CVE-2026-64650", "severity": "medium", "published": "2026-07-20T20:16:06Z" }, { "ghsa": "GHSA-g48p-5rr5-8rgq", "cve": "CVE-2026-64651", "severity": "medium", "published": "2026-07-20T20:15:50Z" } ], "replies": { "sampled": 25, "unanswered": 14, "medianDays": 0.1 } }, "updatedAt": "2026-11-07T18:22:06.975781508Z" } }, "answer": "Vertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against Vercel AI Gateway's 67.8 (B), and leads in every scored category.", "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": 1486, "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": "2026-11-07T18:21:03.779025658Z", "lastOk": true, "lastStatus": 404, "lastMs": 763, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 118, "p95ms24h": 752, "samples24h": 200, "samples30d": 200, "days": [ { "date": "2026-11-06", "probes": 13, "ok": 13 }, { "date": "2026-11-07", "probes": 187, "ok": 187 } ] }, "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": "2026-11-07T18:21:03.779025658Z" } }, "edges": [ { "by": 20, "category": "reliability", "leads": "vertex-ai", "name": "Reliability", "reasons": { "a": "Hosted reading. AI Gateway is a component on www.vercel-status.com (20). The history feed, re-read on 1 November 2026, has 25 entries from 23 July to 23 October, so it covers the whole 90 days from 3 August. None names AI Gateway in its title or text. The Drains, Logs and Observability incidents (6, 17 and 20 August, 16 to 17 September, 10 October in Washington, which names delayed logs, metrics and traces in general, and 23 October) name no AI Gateway surface, and none reports requests failing. Component tags sit in the status API, which robots.txt disallows, so they were not used. A readable page that posts incidents, none touching the product, is a clean record, as vercel-connect's incidents were read from the same feed (30). The rate-limit page, re-read on 1 November, says it describes behaviour rather than fixed numbers. The paid tier has no gateway limit, and the free tier's per-model limits are not published (5 of 15). A 429 has a documented JSON body, some carry `retry-after`, the docs give backoff code and separate a 429 from a 402 budget rejection, and failed provider attempts are retried on other providers (14 of 15). The Enterprise SLA excludes the APIs and CLI, and no SLA naming AI Gateway was found (0). Generally available since 21 August 2025. Token Pass is early access and the Python SDK is in beta (10).", "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": 79, "b": 99 } }, { "by": 20, "category": "schema", "leads": "vertex-ai", "name": "Schema \u0026 documentation", "reasons": { "a": "Router, scored on the API lines. Vercel's OpenAPI 3.0.3 document has AI Gateway management paths (budgets, routing rules, virtual model configs, routers) and `POST /api-keys`. It does not cover the inference routes on ai-gateway.vercel.sh or `/v1/models`, `/v1/credits`, `/v1/generation` and `/v1/report`, which follow the OpenAI and Anthropic formats and the REST reference page (12 of 25). Every docs page is served as Markdown, and vercel.com/llms.txt lists AI Gateway and the keyless model list (10). The docs say when to use AI Gateway, which API format suits which client, and what each control leaves out, such as BYOK spend outside budgets (16 of 20). `providerOptions.gateway` fields are documented in tables with types, and the model list names each model's supported parameters. The request bodies have no published schema of their own (9 of 15). cURL, TypeScript and Python examples on most pages, and error tables in the FAQ, the REST reference and the Token Pass pages. The Chat Completions error list omits 402 (13 of 15). Paths carry `/v1`, the changelog is dated, with 95 entries naming AI Gateway from 3 August to 30 October 2026, and `@ai-sdk/gateway` keeps a CHANGELOG. The changelog sitemap dates one AI Gateway entry to 25 March 2025, before the alpha (14 of 15).", "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": 74, "b": 94 } }, { "by": 20, "category": "payments", "leads": "vertex-ai", "name": "Payments \u0026 pricing", "reasons": { "a": "No x402, MPP or L402 (0). Per-token prices for every model are public in the keyless model list and the catalogue, and add-on prices are on the pricing page (20). A monthly free credit exists, but the getting-started page and the FAQ say the team must add a valid payment method before using it (0). A person signs up in a browser. Keys can then be created through `POST /v1/api-keys`, which needs a Vercel access token from that account (0).", "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": 20, "b": 40 } }, { "by": 19, "category": "transparency", "leads": "vertex-ai", "name": "Transparency \u0026 trust", "reasons": { "a": "Closed service under the Terms of Service last updated 19 October 2026, the AI Product Terms with an AI Gateway section, and Token Pass terms on its docs page. Routed models carry the terms of 64 providers listed in the Notices and Licence Information, and the SDK is Apache-2.0 (18 of 30). The FAQ, the ZDR page and the logs page agree that prompt and response content is not kept. The terms place content sent to providers under the providers' own terms, give the no-training warranty only to Enterprise and bar sensitive personal information in Input. The DPA covers Pro and Enterprise, not Hobby, and the privacy notice gives retention criteria, not periods (17 of 30). No deprecation policy found. Model retirements carry dates in the model list, and the AI Product Terms let Vercel change fees, change or end anything in beta without notice, and end Token Pass with a pro-rata refund (8 of 20). Provider terms are listed per provider and regional inference names four regions, while the gateway itself may process a request in any Vercel region. The subprocessor list on security.vercel.com was not read (12 of 20).", "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": 71, "b": 90 } }, { "by": 18, "category": "security", "leads": "vertex-ai", "name": "Security \u0026 auth", "reasons": { "a": "Router, read on the model lines. AI Gateway API keys belong to a team, can be limited to one project and given an expiry and a budget, are deactivated when their creator leaves the team, and can be revoked without authentication by reporting a leaked key. Keys carry no per-model or read-only scope apart from the Token Pass key type. On Vercel, project OIDC tokens replace long-lived keys (24 of 30). Vercel says it does not train on prompts, and the AI Product Terms make that a warranty only for Enterprise subscriptions. Provider training is filtered only when `disallowPromptTraining` or ZDR is set, the filter does not apply to BYOK, and the terms say Stealth Model providers may train on inputs (12 of 20). The gateway does not keep prompt or response content. Provider ZDR is free per request on Pro and Enterprise and not available on Hobby, and BYOK keys are skipped under ZDR unless marked (12 of 15). Per-request logs record status, provider attempts, tokens, cost and authentication method, with routing details kept 30 days and Trace Drains and spend reports on paid plans (13 of 15). Valid security.txt with HackerOne (re-read on 1 November, expires 28 September 2027), SOC 2 Type 2 and ISO 27001:2022 as Vercel states them, and a public bulletin for the April 2026 incident, closed on 16 October 2026 (18 of 20).", "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": 79, "b": 97 } }, { "by": 14, "category": "ergonomics", "leads": "vertex-ai", "name": "Agent ergonomics", "reasons": { "a": "Router, read on the model lines. Tool calling is documented on all six surfaces and 303 of 498 models carry the tool-use tag on 1 November, with behaviour depending on the model routed (16 of 20). Structured output is documented per surface and tagged on 278 models (13 of 15). `caching: 'auto'` adds Anthropic cache markers, `cache_ttl` asks for one-hour entries, `x-session-affinity` keeps a conversation on one provider, and cache-read prices are listed per model (14 of 15). 162 models list a context of one million tokens or more, a judgement call since a router has no default model (15). The SDK source has a `gateway-batch.ts` file, but no batch endpoint or batch discount was found in the docs (2 of 10). The AI SDK for TypeScript, the AI SDK for Python in beta, and the OpenAI and Anthropic SDKs with a changed base URL (10). Errors return `message` and `type`, an exceeded budget answers 402 apart from a 429, the SDK has ten typed `Gateway*Error` classes, and the FAQ maps each status to a fix (13 of 15).", "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": 83, "b": 97 } } ], "facts": [ { "a": "Model router", "b": "Model API", "name": "Kind" }, { "a": "Vercel Inc.", "b": "Google Cloud", "name": "Vendor" }, { "a": "https://ai-gateway.vercel.sh/v1", "b": "https://aiplatform.googleapis.com/v1", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "OAuth or key", "b": "OAuth or key", "name": "Auth" }, { "a": "Pay per use", "b": "Pay per use", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Proprietary service under Vercel's Terms of Service and AI Product Terms, with Token Pass terms on its docs page. Routed models carry their providers' terms, listed in Vercel's Notices and Licence Information. The `@ai-sdk/gateway` provider is Apache-2.0", "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": "2026-10-30", "b": "2026-11-05", "name": "Last release" }, { "a": "2026-06-01", "b": "2026-09-02", "name": "Terms last updated" }, { "a": "2026-06-01", "b": "2026-10-01", "name": "Privacy policy last updated" }, { "a": "yes, with an opt-out", "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": "yes", "b": "not found in the text", "name": "Arbitration or class-action waiver" }, { "a": "29.6M npm/wk", "b": "20.9M PyPI/wk", "name": "Popularity" }, { "a": "3/5 (4)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "Vertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against Vercel AI Gateway's 67.8 (B), and leads in every scored category.", "question": "Which is better for AI agents, Vercel AI Gateway or Vertex AI (Gemini Enterprise Agent Platform)?" }, { "answer": "Both take an API key or an OAuth sign-in.", "question": "Do Vercel AI Gateway and Vertex AI (Gemini Enterprise Agent Platform) need an API key?" }, { "answer": "Yes. Vercel AI Gateway has a hosted endpoint at https://ai-gateway.vercel.sh/v1 and Vertex AI (Gemini Enterprise Agent Platform) at https://aiplatform.googleapis.com/v1.", "question": "Can an agent call Vercel AI Gateway and Vertex AI (Gemini Enterprise Agent Platform) without installing anything?" } ], "goodFor": [ { "aheadOn": null, "also": null, "goodFor": "Teams that want one key, one bill, budgets and failover in front of many model providers, especially on Vercel with OIDC.", "slug": "vercel-ai-gateway", "watchFor": "The free monthly credit needs a valid payment method on the team, and its amount is not stated in the reviewed docs" }, { "aheadOn": [ "Reliability, 99 against 79", "Schema \u0026 documentation, 94 against 74", "Agent ergonomics, 97 against 83", "Security \u0026 auth, 97 against 79", "Payments \u0026 pricing, 40 against 20", "Maintenance \u0026 community, 91 against 79", "Transparency \u0026 trust, 90 against 71" ], "also": [ "Agent-ready, a grade of BB or better", "Free to start without a card", "No incidents deducted, where Vercel AI Gateway 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": { "vercel-ai-gateway": [ { "causes": [ "correction" ], "date": "2026-11-01", "delta": 1, "from": 66.8, "fromGrade": "B", "to": 67.8, "toGrade": "B" }, { "causes": [ "method" ], "date": "2026-10-27", "delta": 0.1, "from": 66.7, "fromGrade": "B", "to": 66.8, "toGrade": "B" } ], "vertex-ai": null }, "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-vercel-ai-gateway.json", "title": "Amazon Bedrock vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-vertex-ai.json", "title": "Amazon Bedrock vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-vercel-ai-gateway.json", "title": "Claude API vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-vertex-ai.json", "title": "Claude API vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-vertex-ai.json", "title": "Antseed vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/antseed-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-vercel-ai-gateway.json", "title": "Azure OpenAI in Foundry Models vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-vertex-ai.json", "title": "Azure OpenAI in Foundry Models vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-vercel-ai-gateway.json", "title": "BlockRun.AI vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-vertex-ai.json", "title": "BlockRun.AI vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-vercel-ai-gateway.json", "title": "Cerebras Inference vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-vertex-ai.json", "title": "Cerebras Inference vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-vercel-ai-gateway.json", "title": "Cloudflare AI Gateway vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-vertex-ai.json", "title": "Cloudflare AI Gateway vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-vercel-ai-gateway.json", "title": "Cloudflare Workers AI vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-vertex-ai.json", "title": "Cloudflare Workers AI vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-vercel-ai-gateway.json", "title": "Cohere Chat API (Command models) vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-vertex-ai.json", "title": "Cohere Chat API (Command models) vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/deepinfra-vs-vercel-ai-gateway.json", "title": "DeepInfra vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/deepinfra-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/deepinfra-vs-vertex-ai.json", "title": "DeepInfra vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/deepinfra-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-vercel-ai-gateway.json", "title": "DeepSeek API vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-vertex-ai.json", "title": "DeepSeek API vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-vertex-ai.json", "title": "Eden AI vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-vercel-ai-gateway.json", "title": "Glimpse vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-vertex-ai.json", "title": "Glimpse vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-vercel-ai-gateway.json", "title": "Fireworks AI Inference vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-vertex-ai.json", "title": "Fireworks AI Inference vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/gemini-api-vs-vercel-ai-gateway.json", "title": "Gemini Developer API vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/gemini-api-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/gemini-api-vs-vertex-ai.json", "title": "Gemini Developer API vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/gemini-api-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-vercel-ai-gateway.json", "title": "GroqCloud vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/groq-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-vertex-ai.json", "title": "GroqCloud vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/groq-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vertex-ai.json", "title": "Hugging Face Inference Providers vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-vercel-ai-gateway.json", "title": "Inkling 2 Small vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-vertex-ai.json", "title": "Inkling 2 Small vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/jais-3-vs-vercel-ai-gateway.json", "title": "Jais 3 vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/jais-3-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/jais-3-vs-vertex-ai.json", "title": "Jais 3 vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/jais-3-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-vercel-ai-gateway.json", "title": "Meta Model API vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-vertex-ai.json", "title": "Meta Model API vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/minimax-api-vs-vercel-ai-gateway.json", "title": "MiniMax API vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/minimax-api-vs-vertex-ai.json", "title": "MiniMax API vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-vercel-ai-gateway.json", "title": "Mistral AI API vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-vertex-ai.json", "title": "Mistral AI API vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-vercel-ai-gateway.json", "title": "Muse Spark Open vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-vertex-ai.json", "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/nemotron-3-5-super-vl-vs-vercel-ai-gateway.json", "title": "Nemotron 3.5 Super VL vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-vercel-ai-gateway.json", "title": "Novita AI vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-vercel-ai-gateway" }, { "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-vercel-ai-gateway.json", "title": "OpenAI API vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/openai-api-vs-vercel-ai-gateway" }, { "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-vercel-ai-gateway.json", "title": "OpenRouter vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/openrouter-vs-vercel-ai-gateway" }, { "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-vercel-ai-gateway.json", "title": "Beam 1.0 vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-vercel-ai-gateway" }, { "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-vercel-ai-gateway.json", "title": "SambaCloud vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/sambanova-vs-vercel-ai-gateway" }, { "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-vercel-ai-gateway.json", "title": "SiliconFlow vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/siliconflow-vs-vercel-ai-gateway" }, { "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-vercel-ai-gateway.json", "title": "Simplismart vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/simplismart-vs-vercel-ai-gateway" }, { "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-vercel-ai-gateway.json", "title": "StepFun API vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/stepfun-api-vs-vercel-ai-gateway" }, { "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-vercel-ai-gateway.json", "title": "SWE-2 Flash vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/swe-2-flash-vs-vercel-ai-gateway" }, { "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-vercel-ai-gateway.json", "title": "Together AI Inference vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/together-inference-vs-vercel-ai-gateway" }, { "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-xai-api.json", "title": "Vercel AI Gateway vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/vercel-ai-gateway-vs-xai-api" }, { "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-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/eden-ai-vs-vercel-ai-gateway.json", "title": "Eden AI vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vercel-ai-gateway.json", "title": "Hugging Face Inference Providers vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/litellm-vs-vercel-ai-gateway.json", "title": "LiteLLM vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/litellm-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/ramp-router-vs-vercel-ai-gateway.json", "title": "Router.com (Ramp Router) vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/ramp-router-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/routerplus-vs-vercel-ai-gateway.json", "title": "RouterPlus vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/routerplus-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/tencent-tokenhub-vs-vercel-ai-gateway.json", "title": "Tencent Cloud TokenHub vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/tencent-tokenhub-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" }, { "json": "https://www.anchorterminal.com/compare/prism-inference-vs-vercel-ai-gateway.json", "title": "Prism Inference vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/prism-inference-vs-vercel-ai-gateway" } ], "panel": null, "scores": [ { "by": 20, "edge": "vertex-ai", "key": "reliability", "name": "Reliability", "vercel-ai-gateway": 79, "vertex-ai": 99, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 20, "edge": "vertex-ai", "key": "schema", "name": "Schema \u0026 documentation", "vercel-ai-gateway": 74, "vertex-ai": 94, "weight": 13 }, { "by": 14, "edge": "vertex-ai", "key": "ergonomics", "name": "Agent ergonomics", "vercel-ai-gateway": 83, "vertex-ai": 97, "weight": 13 }, { "by": 18, "edge": "vertex-ai", "key": "security", "name": "Security \u0026 auth", "vercel-ai-gateway": 79, "vertex-ai": 97, "weight": 14 }, { "by": 20, "edge": "vertex-ai", "key": "payments", "name": "Payments \u0026 pricing", "vercel-ai-gateway": 20, "vertex-ai": 40, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 12, "edge": "vertex-ai", "key": "maintenance", "name": "Maintenance \u0026 community", "vercel-ai-gateway": 79, "vertex-ai": 91, "weight": 7 }, { "by": 19, "edge": "vertex-ai", "key": "transparency", "name": "Transparency \u0026 trust", "vercel-ai-gateway": 71, "vertex-ai": 90, "weight": 7 } ], "summary": "Vertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against Vercel AI Gateway's 67.8 (B), and leads in every scored category. Both do llm inference.", "tasks": null, "tutorials": [], "verdicts": { "vercel-ai-gateway": "Token prices pass through with no markup, prompts are not stored by the gateway, and budgets, provider failover and per-request logs are built in. The free monthly credit needs a card on file, rate limits are not published as numbers, no SLA covers the API, and the contractual promise not to train on content applies to Enterprise subscriptions only.", "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/vercel-ai-gateway-vs-vertex-ai", "json": "https://www.anchorterminal.com/compare/vercel-ai-gateway-vs-vertex-ai.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/vercel-ai-gateway-vs-vertex-ai.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/vercel-ai-gateway-vs-vertex-ai.min.md" }, "markdown": "Vertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against Vercel AI Gateway's 67.8 (B), and leads in every scored category. Both do llm inference.\n\n- Vercel AI Gateway: grade B, 67.8/100, rank #302 of 1486. Markdown https://www.anchorterminal.com/tools/vercel-ai-gateway.md · JSON https://www.anchorterminal.com/api/v1/tools/vercel-ai-gateway.json\n- Vertex AI (Gemini Enterprise Agent Platform): grade AA, 88.7/100, rank #2 of 1486. 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### Vercel AI Gateway (B)\n\nGood for: Teams that want one key, one bill, budgets and failover in front of many model providers, especially on Vercel with OIDC.\n\nWatch for: The free monthly credit needs a valid payment method on the team, and its amount is not stated in the reviewed docs\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 79\n- Schema \u0026 documentation, 94 against 74\n- Agent ergonomics, 97 against 83\n- Security \u0026 auth, 97 against 79\n- Payments \u0026 pricing, 40 against 20\n- Maintenance \u0026 community, 91 against 79\n- Transparency \u0026 trust, 90 against 71\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n- Free to start without a card\n- No incidents deducted, where Vercel AI Gateway 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### Reliability: Vertex AI (Gemini Enterprise Agent Platform) +20\n\n- Vercel AI Gateway (79): Hosted reading. AI Gateway is a component on www.vercel-status.com (20). The history feed, re-read on 1 November 2026, has 25 entries from 23 July to 23 October, so it covers the whole 90 days from 3 August. None names AI Gateway in its title or text. The Drains, Logs and Observability incidents (6, 17 and 20 August, 16 to 17 September, 10 October in Washington, which names delayed logs, metrics and traces in general, and 23 October) name no AI Gateway surface, and none reports requests failing. Component tags sit in the status API, which robots.txt disallows, so they were not used. A readable page that posts incidents, none touching the product, is a clean record, as vercel-connect's incidents were read from the same feed (30). The rate-limit page, re-read on 1 November, says it describes behaviour rather than fixed numbers. The paid tier has no gateway limit, and the free tier's per-model limits are not published (5 of 15). A 429 has a documented JSON body, some carry `retry-after`, the docs give backoff code and separate a 429 from a 402 budget rejection, and failed provider attempts are retried on other providers (14 of 15). The Enterprise SLA excludes the APIs and CLI, and no SLA naming AI Gateway was found (0). Generally available since 21 August 2025. Token Pass is early access and the Python SDK is in beta (10).\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### Schema \u0026 documentation: Vertex AI (Gemini Enterprise Agent Platform) +20\n\n- Vercel AI Gateway (74): Router, scored on the API lines. Vercel's OpenAPI 3.0.3 document has AI Gateway management paths (budgets, routing rules, virtual model configs, routers) and `POST /api-keys`. It does not cover the inference routes on ai-gateway.vercel.sh or `/v1/models`, `/v1/credits`, `/v1/generation` and `/v1/report`, which follow the OpenAI and Anthropic formats and the REST reference page (12 of 25). Every docs page is served as Markdown, and vercel.com/llms.txt lists AI Gateway and the keyless model list (10). The docs say when to use AI Gateway, which API format suits which client, and what each control leaves out, such as BYOK spend outside budgets (16 of 20). `providerOptions.gateway` fields are documented in tables with types, and the model list names each model's supported parameters. The request bodies have no published schema of their own (9 of 15). cURL, TypeScript and Python examples on most pages, and error tables in the FAQ, the REST reference and the Token Pass pages. The Chat Completions error list omits 402 (13 of 15). Paths carry `/v1`, the changelog is dated, with 95 entries naming AI Gateway from 3 August to 30 October 2026, and `@ai-sdk/gateway` keeps a CHANGELOG. The changelog sitemap dates one AI Gateway entry to 25 March 2025, before the alpha (14 of 15).\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### Payments \u0026 pricing: Vertex AI (Gemini Enterprise Agent Platform) +20\n\n- Vercel AI Gateway (20): No x402, MPP or L402 (0). Per-token prices for every model are public in the keyless model list and the catalogue, and add-on prices are on the pricing page (20). A monthly free credit exists, but the getting-started page and the FAQ say the team must add a valid payment method before using it (0). A person signs up in a browser. Keys can then be created through `POST /v1/api-keys`, which needs a Vercel access token from that account (0).\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### Transparency \u0026 trust: Vertex AI (Gemini Enterprise Agent Platform) +19\n\n- Vercel AI Gateway (71): Closed service under the Terms of Service last updated 19 October 2026, the AI Product Terms with an AI Gateway section, and Token Pass terms on its docs page. Routed models carry the terms of 64 providers listed in the Notices and Licence Information, and the SDK is Apache-2.0 (18 of 30). The FAQ, the ZDR page and the logs page agree that prompt and response content is not kept. The terms place content sent to providers under the providers' own terms, give the no-training warranty only to Enterprise and bar sensitive personal information in Input. The DPA covers Pro and Enterprise, not Hobby, and the privacy notice gives retention criteria, not periods (17 of 30). No deprecation policy found. Model retirements carry dates in the model list, and the AI Product Terms let Vercel change fees, change or end anything in beta without notice, and end Token Pass with a pro-rata refund (8 of 20). Provider terms are listed per provider and regional inference names four regions, while the gateway itself may process a request in any Vercel region. The subprocessor list on security.vercel.com was not read (12 of 20).\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### Security \u0026 auth: Vertex AI (Gemini Enterprise Agent Platform) +18\n\n- Vercel AI Gateway (79): Router, read on the model lines. AI Gateway API keys belong to a team, can be limited to one project and given an expiry and a budget, are deactivated when their creator leaves the team, and can be revoked without authentication by reporting a leaked key. Keys carry no per-model or read-only scope apart from the Token Pass key type. On Vercel, project OIDC tokens replace long-lived keys (24 of 30). Vercel says it does not train on prompts, and the AI Product Terms make that a warranty only for Enterprise subscriptions. Provider training is filtered only when `disallowPromptTraining` or ZDR is set, the filter does not apply to BYOK, and the terms say Stealth Model providers may train on inputs (12 of 20). The gateway does not keep prompt or response content. Provider ZDR is free per request on Pro and Enterprise and not available on Hobby, and BYOK keys are skipped under ZDR unless marked (12 of 15). Per-request logs record status, provider attempts, tokens, cost and authentication method, with routing details kept 30 days and Trace Drains and spend reports on paid plans (13 of 15). Valid security.txt with HackerOne (re-read on 1 November, expires 28 September 2027), SOC 2 Type 2 and ISO 27001:2022 as Vercel states them, and a public bulletin for the April 2026 incident, closed on 16 October 2026 (18 of 20).\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### Agent ergonomics: Vertex AI (Gemini Enterprise Agent Platform) +14\n\n- Vercel AI Gateway (83): Router, read on the model lines. Tool calling is documented on all six surfaces and 303 of 498 models carry the tool-use tag on 1 November, with behaviour depending on the model routed (16 of 20). Structured output is documented per surface and tagged on 278 models (13 of 15). `caching: 'auto'` adds Anthropic cache markers, `cache_ttl` asks for one-hour entries, `x-session-affinity` keeps a conversation on one provider, and cache-read prices are listed per model (14 of 15). 162 models list a context of one million tokens or more, a judgement call since a router has no default model (15). The SDK source has a `gateway-batch.ts` file, but no batch endpoint or batch discount was found in the docs (2 of 10). The AI SDK for TypeScript, the AI SDK for Python in beta, and the OpenAI and Anthropic SDKs with a changed base URL (10). Errors return `message` and `type`, an exceeded budget answers 402 apart from a 429, the SDK has ten typed `Gateway*Error` classes, and the FAQ maps each status to a fix (13 of 15).\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## Score by category\n\n| Category | Weight | Vercel AI Gateway | Vertex AI (Gemini Enterprise Agent Platform) | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 79 | 99 | Vertex AI (Gemini Enterprise Agent Platform) +20 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 74 | 94 | Vertex AI (Gemini Enterprise Agent Platform) +20 |\n| Agent ergonomics | 13% (16.2 this run) | 83 | 97 | Vertex AI (Gemini Enterprise Agent Platform) +14 |\n| Security \u0026 auth | 14% (17.5 this run) | 79 | 97 | Vertex AI (Gemini Enterprise Agent Platform) +18 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 40 | Vertex AI (Gemini Enterprise Agent Platform) +20 |\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) | 71 | 90 | Vertex AI (Gemini Enterprise Agent Platform) +19 |\n| Negative events | ≤15 | -3 | 0 | |\n| **Total** | | **67.8 · B** | **88.7 · AA** | |\n\n## Facts side by side\n\n| Fact | Vercel AI Gateway | Vertex AI (Gemini Enterprise Agent Platform) |\n| --- | --- | --- |\n| Kind | Model router | Model API |\n| Vendor | Vercel Inc. | Google Cloud |\n| Hosted endpoint | `https://ai-gateway.vercel.sh/v1` | `https://aiplatform.googleapis.com/v1` |\n| Transports | HTTP | HTTP |\n| Auth | OAuth or key | OAuth or key |\n| Pricing | Pay per use | Pay per use |\n| x402 | no | no |\n| Licence | Proprietary service under Vercel's Terms of Service and AI Product Terms, with Token Pass terms on its docs page. Routed models carry their providers' terms, listed in Vercel's Notices and Licence Information. The `@ai-sdk/gateway` provider is Apache-2.0 | 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 | 2026-10-30 | 2026-11-05 |\n| Terms last updated | 2026-06-01 | 2026-09-02 |\n| Privacy policy last updated | 2026-06-01 | 2026-10-01 |\n| Customer content may train models | yes, with an opt-out | 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 | yes | not found in the text |\n| Popularity | 29.6M npm/wk | 20.9M PyPI/wk |\n| Agent reviews | 3/5 (4) | none |\n\n## How the scores have moved\n\n### Vercel AI Gateway\n\n- +1.0 on 1 November 2026: correction\n- +0.1 on 27 October 2026: checklist\n\n### Vertex AI (Gemini Enterprise Agent Platform)\n\nNo score change since it was listed.\n\n## Verdicts\n\n**Vercel AI Gateway.** Token prices pass through with no markup, prompts are not stored by the gateway, and budgets, provider failover and per-request logs are built in. The free monthly credit needs a card on file, rate limits are not published as numbers, no SLA covers the API, and the contractual promise not to train on content applies to Enterprise subscriptions only.\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### Vercel AI Gateway\n\n1. Read `GET https://ai-gateway.vercel.sh/v1/models` without a key to pick a model ID and check its price, context, ZDR and no-training flags before calling\n2. Set `zeroDataRetention` or `disallowPromptTraining` to true in `providerOptions.gateway` on sensitive requests. Default routing ignores provider retention and training policies\n3. Treat a 429 as retryable and honour `retry-after` when present. A 402 with `quota_for_entity_exceeded` is a spent budget, so do not retry it\n4. On a Token Pass key, a 403 with `no_providers_available` means spent credit or a model outside the pass. Retry with a standard AI Gateway key, which bills credits\n5. Set `inferenceRegion` when data residency matters. The default `global` may run inference outside the user's jurisdiction\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, Vercel AI Gateway or Vertex AI (Gemini Enterprise Agent Platform)?\n\nVertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against Vercel AI Gateway's 67.8 (B), and leads in every scored category.\n\n### Do Vercel AI Gateway and Vertex AI (Gemini Enterprise Agent Platform) need an API key?\n\nBoth take an API key or an OAuth sign-in.\n\n### Can an agent call Vercel AI Gateway and Vertex AI (Gemini Enterprise Agent Platform) without installing anything?\n\nYes. Vercel AI Gateway has a hosted endpoint at https://ai-gateway.vercel.sh/v1 and Vertex AI (Gemini Enterprise Agent Platform) at https://aiplatform.googleapis.com/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/vercel-ai-gateway-vs-vertex-ai.json, and with the fewest tokens: https://www.anchorterminal.com/compare/vercel-ai-gateway-vs-vertex-ai.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"vercel-ai-gateway\", \"b\": \"vertex-ai\"}`. From a terminal: `anchor compare vercel-ai-gateway vertex-ai`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/vercel-ai-gateway.json and https://www.anchorterminal.com/api/v1/tools/vertex-ai.json\n\n## Other comparisons with Vercel AI Gateway or Vertex AI (Gemini Enterprise Agent Platform)\n\n- [Amazon Bedrock vs Vercel AI Gateway](https://www.anchorterminal.com/compare/amazon-bedrock-vs-vercel-ai-gateway.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 Vercel AI Gateway](https://www.anchorterminal.com/compare/anthropic-api-vs-vercel-ai-gateway.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 Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/antseed-vs-vertex-ai.md)\n- [Azure OpenAI in Foundry Models vs Vercel AI 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Providers vs Vercel AI Gateway](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vercel-ai-gateway.md)\n- [LiteLLM vs Vercel AI Gateway](https://www.anchorterminal.com/compare/litellm-vs-vercel-ai-gateway.md)\n- [Router.com (Ramp Router) vs Vercel AI Gateway](https://www.anchorterminal.com/compare/ramp-router-vs-vercel-ai-gateway.md)\n- [RouterPlus vs Vercel AI Gateway](https://www.anchorterminal.com/compare/routerplus-vs-vercel-ai-gateway.md)\n- [Tencent Cloud TokenHub vs Vercel AI Gateway](https://www.anchorterminal.com/compare/tencent-tokenhub-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- [Prism Inference vs Vercel AI Gateway](https://www.anchorterminal.com/compare/prism-inference-vs-vercel-ai-gateway.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": "Vercel AI Gateway vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "" } ], "description": "Vertex AI scores 88.7 (AA) to Vercel AI Gateway's 67.8 (B) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Vercel AI Gateway B 67.8", "Vertex AI (Gemini Enterprise Agent Platform) AA 88.7", "scores" ], "h1": "Vercel AI Gateway vs Vertex AI (Gemini Enterprise Agent Platform)", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/vercel-ai-gateway-vs-vertex-ai", "published": "2026-10-01", "section": "tools", "title": "Vercel AI Gateway vs Vertex AI for AI agents (2026) | Anchor Terminal", "toc": null, "updated": "2026-11-07", "url": "https://www.anchorterminal.com/compare/vercel-ai-gateway-vs-vertex-ai" }, "tokens": { "markdown": 7950, "slim": 3930 }, "version": 1 }