{ "data": { "a": { "slug": "ramp-router", "name": "Router.com (Ramp Router)", "vendor": "Ramp", "vendorUrl": "https://router.com", "kind": "router", "category": "inference", "summary": "Router.com (Ramp Router) is Ramp's LLM gateway. One API key reaches OpenAI, Anthropic, xAI and open-weight models through OpenAI Responses, Chat Completions and Anthropic Messages endpoints, with fallbacks, Flex-tier routing, shadow testing and benchmark aliases.", "url": "https://www.anchorterminal.com/tools/ramp-router", "markdownUrl": "https://www.anchorterminal.com/tools/ramp-router.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/ramp-router.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/ramp-router.json", "dns": "ramp-router.grade.anchorterminal.com", "repo": "https://github.com/ramp-public/ramp-cli", "license": "Closed service under the Router Terms of Service (last updated 31 August 2026). The Ramp CLI that configures coding agents for Router is MIT.", "transports": [ "http" ], "remoteUrl": "https://api.router.com/v1", "packages": [ { "registry": "npm", "name": "@ramp/router" } ], "auth": "api-key", "authNotes": "A Router API key, sent as `Authorization: Bearer` or `X-Api-Key`. A person signs up in the browser with Sign in with Ramp, or by email or Google with a business email address on a business domain (Gmail, Outlook, iCloud, Proton and similar are refused); other people can ask router@ramp.com for manual onboarding. Keys are created on the dashboard's API keys page and shown once, or by the Ramp CLI after browser approval. Each key can carry a lifetime or periodic spend cap and be locked, unlocked or revoked (https://docs.router.com/api/endpoint.md, https://docs.router.com/resources/signup-eligibility.md).", "pricing": "usage", "pricingNotes": "Routing is free through 2026, and models are billed at list price per 1M tokens from account credit. Router.com says the first $26 of credits are free. Requests served with the caller's own provider keys carry no Router charge, unless they fall back to Router's shared key. No routing price after 2026 was found. Per-model prices are public at https://router.com/models and https://docs.router.com/supported-models.md.", "priceSummary": "0% fee", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs at https://docs.router.com (all 41 Markdown pages read on 27 October 2026). Calls draw on account credit, and a 402 means the account has no available credit.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": 1667, "pypiWeekly": null, "asOf": "2026-10-27" }, "docsUrl": "https://docs.router.com", "llmsTxt": "https://docs.router.com/llms.txt", "capabilities": [ "inference.router", "inference.llm", "inference.decision" ], "tags": [ "hosted", "router", "closed-source", "usage-priced", "prepaid", "free-credit", "llms-txt", "openai-compatible", "anthropic-compatible", "streaming", "prompt-caching", "cli", "new" ], "lastRelease": "2026-11-03", "graded": true, "anchor": { "graded": true, "score": 53.7, "grade": "D", "agentReady": false, "rank": 936, "ranked": true, "rankOf": 1486, "categoryRank": 30, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 77, "maintenance": 59, "payments": 40, "reliability": 22, "schema": 58, "security": 66, "transparency": 64 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-04" }, "negative": 0, "verdict": "Detailed Markdown docs with typed error codes, per-model capability data and routing an agent can set per request. No OpenAPI document, status page, changelog or published rate limits were found. Signup needs a US business email in a browser, and Ramp records prompts and outputs for a year by default unless switched off.", "bestFor": "Teams in the US that want one key for OpenAI, Anthropic, xAI and open-weight models, with routing to cheaper tiers and per-request cost, and can switch off content recording.", "strengths": [ "llms.txt and a Markdown copy of every docs page, with a field table for each endpoint and an error reference with an action per code", "`GET /v1/models` returns limits, tool, structured-output, caching and reasoning support, and per-provider prices for each model", "Fallback lists of up to 15 provider, model and tier candidates, with timeouts that bound each attempt", "Every response names the serving provider, and Responses calls return `usage.cost` in USD", "Routing is free through 2026, BYOK requests carry no Router charge, and the first $26 of credits are free" ], "weaknesses": [ "Ramp-side content recording is on by default and keeps prompts, outputs and tool calls for one year", "No OpenAPI document, status page, changelog, SLA or published rate limits were found", "Signup needs a US business email domain or Sign in with Ramp, in a browser", "No batch, embeddings or files routes, and Chat Completions lacks fallback lists and cost", "No routing price after 31 December 2026 was found" ], "agentNotes": [ "Switch off content recording in Settings before sending private data. It is on by default and keeps prompts and outputs for a year", "Read model ids from `GET /v1/models` at runtime. Ids are account-specific, an unknown one is a 404, and Gemini ids need your own Google key", "Use `POST /v1/responses` with a `models` list for fallbacks. Router stops falling back once a stream has started", "Set `fallback_timeout` and `provider_timeout`, or `allow_flex_tier: false`, when latency matters. Flex routing is on by default", "Treat both `401 invalid_api_key` and `401 api_key_deactivated` as a possibly locked key, and stop retrying on `402`" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 53.7 } ], "editorialScores": { "ergonomics": 77, "maintenance": 59, "payments": 40, "reliability": 22, "schema": 58, "security": 66, "transparency": 50 }, "provenanceScore": 77, "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": "curl -fsSL https://router.com/install.sh | sh # Ramp CLI, configures Claude Code, Codex, OpenCode, Pi, Hermes or Conductor", "http": "curl https://api.router.com/v1/responses \\\n -H \"Authorization: Bearer $RAMP_ROUTER_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\"models\":[\"openai:gpt-5.4-mini\",\"fireworks:accounts/fireworks/models/kimi-k3\"],\"input\":\"Reply with one word: pong.\",\"max_output_tokens\":16}'" }, "letme": { "capability": "https://letme.dev/inference.router", "tool": "https://letme.dev/ramp-router" }, "area": "models", "unitPrices": [ { "item": "Routing fee", "unit": "pct", "usd": 0, "note": "Free through 2026. Models are billed at list price" }, { "item": "Claude Opus 5.5 input", "unit": "1m-tokens", "usd": 4, "note": "claude-opus-5-5, 1,000,000-token context" }, { "item": "Claude Opus 5.5 output", "unit": "1m-tokens", "usd": 20 }, { "item": "GPT-6.1 Sol input", "unit": "1m-tokens", "usd": 2, "note": "gpt-6.1-sol, 1,050,000-token context" }, { "item": "GPT-6.1 Sol output", "unit": "1m-tokens", "usd": 10 }, { "item": "Kimi K3 input", "unit": "1m-tokens", "usd": 3, "note": "kimi-k3, served by Fireworks or Baseten" }, { "item": "Kimi K3 output", "unit": "1m-tokens", "usd": 15 } ], "provenance": { "legalEntity": "Ramp Business Corporation", "domain": "router.com", "domainRegistered": "1995-07-26", "endpointOnVendorDomain": true, "terms": "https://ramp.com/legal/developer-terms/developer-terms/router-terms-of-service", "privacy": "https://ramp.com/legal/privacy-terms/privacy-terms/router-privacy-notice", "statusPage": "", "changelog": "", "securityTxt": "valid", "checked": "2026-11-04", "notes": [ "The Router Terms of Service page renders only with JavaScript. The legal entity was read from the legal site's script files on 27 October, a reading this run no longer counts, and is kept as recorded pending a ruling.", "The Router Privacy Notice URL linked from router.com answers 301 to Ramp's general privacy policy. The docs FAQ and model pages now link Ramp's general privacy policy directly.", "No status page found. status.router.com does not resolve, router.com/status answers 404, and no status link appears in the docs or on router.com.", "No changelog found. The docs index lists none. The Ramp CLI's tagged releases are the only dated release record.", "router.com/.well-known/security.txt gives security-external@ramp.com as the contact and expires on 18 March 2027.", "router.com robots.txt carries Content-Signal search=yes, ai-input=yes, ai-train=yes.", "RDAP gives router.com a registration date of 26 July 1995 and Cloudflare, Inc. as registrar, per the 27 October check, so the domain predates Ramp. The earlier API host router-api.ramp.com still answered on 27 October." ], "score": 77 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/ramp-router.json", "live": { "slug": "ramp-router", "probe": { "target": "https://api.router.com/v1", "method": "get", "lastAt": "2026-11-07T18:20:49.810567696Z", "lastOk": true, "lastStatus": 401, "lastMs": 486, "lastNote": "asks for credentials", "authRequired": true, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 344, "p95ms24h": 467, "samples24h": 239, "samples30d": 2608, "days": [ { "date": "2026-10-27", "probes": 3, "ok": 3 }, { "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 } ] }, "versions": [ { "registry": "github", "name": "ramp-public/ramp-cli", "version": "v0.2.94", "released": "2026-11-04", "seenAt": "2026-11-07T00:00:15.752300599Z" }, { "registry": "npm", "name": "@ramp/router", "version": "0.2.94", "seenAt": "2026-11-07T00:00:11.293440786Z" } ], "githubStars": 52, "npmWeekly": 1547, "securityTxt": { "url": "https://router.com/.well-known/security.txt", "state": "valid", "expires": "2027-03-18T19:00:00.000Z", "checkedAt": "2026-11-07T16:00:59.76243632Z" }, "llmsTxt": { "url": "https://docs.router.com/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:33:43.463904493Z" }, "domain": { "domain": "router.com", "registered": "1995-07-26", "source": "https://rdap.verisign.com/com/v1/domain/router.com", "checkedAt": "2026-11-01T14:14:03.12738718Z" }, "pages": [ { "url": "https://ramp.com/legal/privacy-terms/privacy-terms/router-privacy-notice", "kind": "privacy", "status": 200, "checkedAt": "2026-11-07T14:18:00.602165915Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "e3b0c44298fc" }, { "url": "https://ramp.com/legal/developer-terms/developer-terms/router-terms-of-service", "kind": "terms", "status": 200, "checkedAt": "2026-11-07T14:17:56.454985663Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "e3b0c44298fc" } ], "github": { "repo": "ramp-public/ramp-cli", "checkedAt": "2026-11-02T08:23:11.9563797Z", "stars": 52, "archived": false, "issuesEnabled": true, "pushedAt": "2026-11-02T03:49:03Z", "openIssues": 2, "openPRs": 5, "issuesOpened90d": 1, "issuesClosed90d": 0, "prsMerged90d": 0, "ci": { "branch": "main", "runs": 50, "success": 30, "failure": 20, "other": 0, "latest": "success", "latestAt": "2026-11-02T04:00:13Z" }, "replies": { "sampled": 2, "unanswered": 2 } }, "updatedAt": "2026-11-07T18:20:49.810567696Z" } }, "answer": "Vertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against Router.com (Ramp Router)'s 53.7 (D), and leads in 6 of 7 scored categories.", "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": 77, "category": "reliability", "leads": "vertex-ai", "name": "Reliability", "reasons": { "a": "Hosted reading. No status page found. status.router.com still does not resolve on 4 November, router.com/status answers 404, and neither the docs nor router.com link one (0). No readable incident history (5). No request or token rate limits are published. The docs say limits vary by model and list only technical limits, a 100 MiB body, 15 candidates and 100 keys per user (0). The errors page passes through provider `retry-after` and `retry-after-ms`, tells clients to respect them, gives a retry or fallback action for every 4xx and 5xx code, says retrying a 501 unchanged won't help and that a failed fallback candidate is not retried, and the fallbacks guide says truncated attempts are billed on top of later attempts. No idempotency key exists for the generation call that starts billing, so this is safe-retry guidance without keys (12). No SLA found in the docs or on router.com (0). The public API carries no beta label in the docs, and the docs llms.txt, re-read on 4 November, still says to treat 'beta pricing, limits, and enterprise controls as subject to change'. A 27 October reading of Ramp's product schedule came from the legal site's script and is no longer counted, so the line keeps its earlier partial value (5 of 10). 0 + 5 + 0 + 12 + 0 + 5 = 22.", "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": 22, "b": 99 } }, { "by": 36, "category": "schema", "leads": "vertex-ai", "name": "Schema \u0026 documentation", "reasons": { "a": "Router, scored on the API lines. No OpenAPI or other machine-readable contract found. /openapi.json on docs.router.com returns the docs app shell. The API follows the OpenAI and Anthropic wire formats, which this checklist doesn't credit to a router, the same reading as RouterPlus (0 of 25). llms.txt and a Markdown copy of every page at the same path with `.md` (10). Pages say which endpoint to prefer and why, what isn't served (embeddings, files, batches), which Chat Completions controls return 501, and which workload suits which job (17 of 20). Router-only fields are tabled with types and bounds, the route selector rules are stated (`model` or `models` but never both, 1 to 15 candidates), over-limit timeouts are a 400 naming the maximum, and the model list documents a typed `router` object with a `schema_version`. Request bodies otherwise follow the upstream formats (12 of 15). curl, OpenAI SDK, Anthropic SDK, LangChain, Vercel AI SDK, LlamaIndex and Pydantic AI examples, and an error reference with a status, code and action for each case (15). Paths sit under `/v1` and the model object is versioned, but no API changelog or dated release notes were found (4 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": 58, "b": 94 } }, { "by": 32, "category": "maintenance", "leads": "vertex-ai", "name": "Maintenance \u0026 community", "reasons": { "a": "Router, read on the model lines for a closed service. The Ramp CLI that ships the `router` commands tagged v0.2.91 on 3 November 2026, a release that changes `router.py` and `router_credentials.py`, one of 81 tags since 6 August (30). Models carry a `deprecated` status and the docs list deprecated and retired models, but no notice period is stated, and the Baseten retirement note gives no date and says requests aren't redirected (4 of 12). Provider-specific Baseten ids and several Fireworks models were retired without dates. The API host moved from router-api.ramp.com to api.router.com, and the old host still answers (3 of 8). No public API changelog. Support is a dashboard button and router@ramp.com, not tested (5 of 15). ramp-cli issue replies were not read, because GitHub's API wasn't available to this session (3 of 10). No API SDK. The Ramp CLI (MIT, npm @ramp/router and @ramp/cli, tagged v0.2.91 in the repository, Homebrew; npm itself not read) sets up agents and keys (7 of 15). The CLI repository has CI, build, npm and router-integration workflows and a tests folder, with 46 commit days since 29 July. ci.yml runs `cargo test` and `pytest` on pushes to main, and the results were not readable (7 of 10).", "b": "Model reading. Gemini Omni 1.2 Flash GA on 5 November, Grok 4.7 GA on 27 October, Gemini 4 Argon GA on 13 October and Claude Haiku 5.5 on 7 October 2026 (30). Stable models stay at least 12 months, and since 6 October Gemini 4 Argon and Gemini 3.8 Flash are in that tier, while 3.7 and 3.6 Flash remain short-term with at least 45 days' notice once a date is set (10 of 12, up from 8). Gemini 2.5 Pro, Flash and Flash-Lite were due to retire on 20 October, three models on one date after more than 12 months, with replacements named. We didn't check partner model retirements (6 of 8, down from 8). Dated release notes on most working days, newest 5 November, and Cloud Customer Care (15). python-genai replies not sampled this run (5 of 10). Current SDKs, google-genai 3.0.0 on 6 November and `@google/genai` 3.0.0, and google-cloud-aiplatform 2.7.0 on 28 October 2026 (15). Supported runtimes stated, Python 3.10 or later and Node 20 or later, per the 6 October check (10). Unchanged at 91." }, "scores": { "a": 59, "b": 91 } }, { "by": 31, "category": "security", "leads": "vertex-ai", "name": "Security \u0026 auth", "reasons": { "a": "Router, read on the model lines. Router keys are shown once, can expire, carry lifetime or periodic spend caps, can be locked, unlocked or revoked, and each key has its own model set and default workload. No permission scopes or programmatic rotation were found (24 of 30). The docs FAQ says Ramp-side content recording is on by default and keeps inputs, outputs and tool calls for one year for debugging, semantic analysis and product improvement, with detected personal data removed before product use. Provider training terms are in Ramp's Provider Schedule, which renders only with JavaScript. Its 27 October reading came from the legal site's script and is no longer counted, so the line is held (6 of 20). Recording can be switched off account-wide, propagating asynchronously and without deleting existing archives, and flagged content may still be kept up to 30 days. The docs FAQ points to the Provider Schedule for zero data retention policies and exceptions, which could not be read, so the line is held (10 of 15). Logs show model, provider, status, tokens, cost, latency, fallback candidates, credential source and routing decisions per request, with usage export to S3 for Router Admins (14 of 15). A valid security.txt on router.com points to Ramp's security address. Ramp's SOC 2 and ISO 27001 reports, per the ramp listing's 8 October check, were not shown to cover Router, which is a separate product under its own terms. No bug bounty found (12 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": 66, "b": 97 } }, { "by": 26, "category": "transparency", "leads": "vertex-ai", "name": "Transparency \u0026 trust", "reasons": { "a": "Closed service. The Router Terms of Service, Router Privacy Notice and Provider Schedule render only with JavaScript. Their 27 October readings came from the legal site's script and are no longer counted, so the lines resting on them are held, as on ramp. The CLI is MIT (16 of 30). The docs FAQ states the one-year default recording, the opt-out and the PII step, and links Ramp's general privacy policy. Every link to the Router Privacy Notice answers 301 to that general policy (16 of 30). No deprecation policy found, and model retirements in the docs carry no dates (5 of 20). The docs FAQ names the providers whose infrastructure runs the models, says all models run on US infrastructure and points to the Provider Schedule for provider retention terms. No Router subprocessor list was found (13 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": 64, "b": 90 } }, { "by": 20, "category": "ergonomics", "leads": "vertex-ai", "name": "Agent ergonomics", "reasons": { "a": "Router, read on the model lines (tool use, structured output, caching, context, batch, SDKs, errors). Tools pass through on Responses, Messages and Chat Completions, and `GET /v1/models` reports `tools.supported` and `parallel` per model, with `null` where Router doesn't know. Behaviour depends on the model (16 of 20). The docs say JSON Schema output is expected to work across providers subject to model support, and each model carries a `structured_outputs` flag. A request the provider can't represent is a 501 (12 of 15). Cache read and write prices per model, a `prompt_cache_key` session lease of 5 or 30 minutes that keeps a session on the provider with a warm cache, and `cache_control` on Messages (14 of 15). Contexts up to 1,050,000 tokens on GPT-6.1 Sol and 1,048,576 on Kimi K3, a judgement call since a router has no default model (15). No batch route; the docs say Router doesn't serve batches (0 of 10). No SDK of its own. The OpenAI and Anthropic SDKs work with a changed base URL, framework setups are documented, and the MIT Ramp CLI configures six coding agents (5 of 10). Typed codes for every error, a `limit` object naming the cap and who set it, an all-candidates-failed summary, request and trace ids on every response and the serving provider in a header (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": 77, "b": 97 } } ], "facts": [ { "a": "Model router", "b": "Model API", "name": "Kind" }, { "a": "Ramp", "b": "Google Cloud", "name": "Vendor" }, { "a": "https://api.router.com/v1", "b": "https://aiplatform.googleapis.com/v1", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "API key", "b": "OAuth or key", "name": "Auth" }, { "a": "Pay per use", "b": "Pay per use", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Closed service under the Router Terms of Service (last updated 31 August 2026). The Ramp CLI that configures coding agents for Router is MIT.", "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": "2026-11-03", "b": "2026-11-05", "name": "Last release" }, { "a": "couldn't be read", "b": "2026-09-02", "name": "Terms last updated" }, { "a": "couldn't be read", "b": "2026-10-01", "name": "Privacy policy last updated" }, { "a": "couldn't be read", "b": "yes", "name": "Customer content may train models" }, { "a": "couldn't be read", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "couldn't be read", "b": "not found in the text", "name": "Terms restrict benchmarking" }, { "a": "couldn't be read", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "couldn't be read", "b": "not found in the text", "name": "Arbitration or class-action waiver" }, { "a": "1.7k 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 Router.com (Ramp Router)'s 53.7 (D), and leads in 6 of 7 scored categories.", "question": "Which is better for AI agents, Router.com (Ramp Router) or Vertex AI (Gemini Enterprise Agent Platform)?" }, { "answer": "Router.com (Ramp Router) needs an API key. Vertex AI (Gemini Enterprise Agent Platform) takes an API key or an OAuth sign-in.", "question": "Do Router.com (Ramp Router) and Vertex AI (Gemini Enterprise Agent Platform) need an API key?" }, { "answer": "Yes. Router.com (Ramp Router) has a hosted endpoint at https://api.router.com/v1 and Vertex AI (Gemini Enterprise Agent Platform) at https://aiplatform.googleapis.com/v1.", "question": "Can an agent call Router.com (Ramp Router) and Vertex AI (Gemini Enterprise Agent Platform) without installing anything?" } ], "goodFor": [ { "aheadOn": null, "also": null, "goodFor": "Teams in the US that want one key for OpenAI, Anthropic, xAI and open-weight models, with routing to cheaper tiers and per-request cost, and can switch off content recording.", "slug": "ramp-router", "watchFor": "Ramp-side content recording is on by default and keeps prompts, outputs and tool calls for one year" }, { "aheadOn": [ "Reliability, 99 against 22", "Schema \u0026 documentation, 94 against 58", "Agent ergonomics, 97 against 77", "Security \u0026 auth, 97 against 66", "Maintenance \u0026 community, 91 against 59", "Transparency \u0026 trust, 90 against 64" ], "also": [ "Agent-ready, a grade of BB or better", "Free to start without a card" ], "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": { "ramp-router": [ { "causes": [ "correction" ], "date": "2026-11-04", "delta": -0.6, "from": 54.3, "fromGrade": "C", "to": 53.7, "toGrade": "D" }, { "causes": [ "method" ], "date": "2026-10-30", "delta": -0.2, "from": 54.5, "fromGrade": "C", "to": 54.3, "toGrade": "C" } ], "vertex-ai": null }, "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-ramp-router.json", "title": "Amazon Bedrock vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-ramp-router" }, { "json": 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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-ramp-router.json", "title": "Inkling 2 Small vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ramp-router" }, { "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-ramp-router.json", "title": "Jais 3 vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/jais-3-vs-ramp-router" }, { "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-ramp-router.json", "title": "Meta Model API vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-ramp-router" }, { "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-ramp-router.json", "title": "MiniMax API vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-ramp-router" }, { "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-ramp-router.json", "title": "Mistral AI API vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-ramp-router" }, { "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-ramp-router.json", "title": "Muse Spark Open vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-ramp-router" }, { "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-ramp-router.json", "title": "Nemotron 3.5 Super VL vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-ramp-router" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-ramp-router.json", "title": "Novita AI vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-ramp-router" }, { "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-ramp-router.json", "title": "OpenAI API vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/openai-api-vs-ramp-router" }, { "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-ramp-router.json", "title": "OpenRouter vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/openrouter-vs-ramp-router" }, { "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-ramp-router.json", "title": "Prism Inference vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/prism-inference-vs-ramp-router" }, { "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-reflection-beam.json", "title": "Router.com (Ramp Router) vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/ramp-router-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/ramp-router-vs-sambanova.json", "title": "Router.com (Ramp Router) vs SambaCloud", "url": "https://www.anchorterminal.com/compare/ramp-router-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/ramp-router-vs-siliconflow.json", "title": "Router.com (Ramp Router) vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/ramp-router-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/ramp-router-vs-simplismart.json", "title": "Router.com (Ramp Router) vs Simplismart", "url": "https://www.anchorterminal.com/compare/ramp-router-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/ramp-router-vs-stepfun-api.json", "title": "Router.com (Ramp Router) vs StepFun API", "url": "https://www.anchorterminal.com/compare/ramp-router-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/ramp-router-vs-swe-2-flash.json", "title": "Router.com (Ramp Router) vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/ramp-router-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/ramp-router-vs-together-inference.json", "title": "Router.com (Ramp Router) vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/ramp-router-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/ramp-router-vs-xai-api.json", "title": "Router.com (Ramp Router) vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/ramp-router-vs-xai-api" }, { "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-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/eden-ai-vs-ramp-router.json", "title": "Eden AI vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-ramp-router" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-ramp-router.json", "title": "Hugging Face Inference Providers vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-ramp-router" }, { "json": "https://www.anchorterminal.com/compare/litellm-vs-ramp-router.json", "title": "LiteLLM vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/litellm-vs-ramp-router" }, { "json": "https://www.anchorterminal.com/compare/ramp-router-vs-routerplus.json", "title": "Router.com (Ramp Router) vs RouterPlus", "url": "https://www.anchorterminal.com/compare/ramp-router-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/ramp-router-vs-tencent-tokenhub.json", "title": "Router.com (Ramp Router) vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/ramp-router-vs-tencent-tokenhub" }, { "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/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": [ { "by": 77, "edge": "vertex-ai", "key": "reliability", "name": "Reliability", "ramp-router": 22, "vertex-ai": 99, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 36, "edge": "vertex-ai", "key": "schema", "name": "Schema \u0026 documentation", "ramp-router": 58, "vertex-ai": 94, "weight": 13 }, { "by": 20, "edge": "vertex-ai", "key": "ergonomics", "name": "Agent ergonomics", "ramp-router": 77, "vertex-ai": 97, "weight": 13 }, { "by": 31, "edge": "vertex-ai", "key": "security", "name": "Security \u0026 auth", "ramp-router": 66, "vertex-ai": 97, "weight": 14 }, { "by": 0, "edge": "", "key": "payments", "name": "Payments \u0026 pricing", "ramp-router": 40, "vertex-ai": 40, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 32, "edge": "vertex-ai", "key": "maintenance", "name": "Maintenance \u0026 community", "ramp-router": 59, "vertex-ai": 91, "weight": 7 }, { "by": 26, "edge": "vertex-ai", "key": "transparency", "name": "Transparency \u0026 trust", "ramp-router": 64, "vertex-ai": 90, "weight": 7 } ], "summary": "Vertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against Router.com (Ramp Router)'s 53.7 (D), and leads in 6 of 7 scored categories. Both do llm inference.", "tasks": null, "tutorials": [], "verdicts": { "ramp-router": "Detailed Markdown docs with typed error codes, per-model capability data and routing an agent can set per request. No OpenAPI document, status page, changelog or published rate limits were found. Signup needs a US business email in a browser, and Ramp records prompts and outputs for a year by default unless switched off.", "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/ramp-router-vs-vertex-ai", "json": "https://www.anchorterminal.com/compare/ramp-router-vs-vertex-ai.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/ramp-router-vs-vertex-ai.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/ramp-router-vs-vertex-ai.min.md" }, "markdown": "Vertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against Router.com (Ramp Router)'s 53.7 (D), and leads in 6 of 7 scored categories. Both do llm inference.\n\n- Router.com (Ramp Router): grade D, 53.7/100, rank #936 of 1486. Markdown https://www.anchorterminal.com/tools/ramp-router.md · JSON https://www.anchorterminal.com/api/v1/tools/ramp-router.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### Router.com (Ramp Router) (D)\n\nGood for: Teams in the US that want one key for OpenAI, Anthropic, xAI and open-weight models, with routing to cheaper tiers and per-request cost, and can switch off content recording.\n\nWatch for: Ramp-side content recording is on by default and keeps prompts, outputs and tool calls for one year\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 22\n- Schema \u0026 documentation, 94 against 58\n- Agent ergonomics, 97 against 77\n- Security \u0026 auth, 97 against 66\n- Maintenance \u0026 community, 91 against 59\n- Transparency \u0026 trust, 90 against 64\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n- Free to start without a card\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) +77\n\n- Router.com (Ramp Router) (22): Hosted reading. No status page found. status.router.com still does not resolve on 4 November, router.com/status answers 404, and neither the docs nor router.com link one (0). No readable incident history (5). No request or token rate limits are published. The docs say limits vary by model and list only technical limits, a 100 MiB body, 15 candidates and 100 keys per user (0). The errors page passes through provider `retry-after` and `retry-after-ms`, tells clients to respect them, gives a retry or fallback action for every 4xx and 5xx code, says retrying a 501 unchanged won't help and that a failed fallback candidate is not retried, and the fallbacks guide says truncated attempts are billed on top of later attempts. No idempotency key exists for the generation call that starts billing, so this is safe-retry guidance without keys (12). No SLA found in the docs or on router.com (0). The public API carries no beta label in the docs, and the docs llms.txt, re-read on 4 November, still says to treat 'beta pricing, limits, and enterprise controls as subject to change'. A 27 October reading of Ramp's product schedule came from the legal site's script and is no longer counted, so the line keeps its earlier partial value (5 of 10). 0 + 5 + 0 + 12 + 0 + 5 = 22.\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) +36\n\n- Router.com (Ramp Router) (58): Router, scored on the API lines. No OpenAPI or other machine-readable contract found. /openapi.json on docs.router.com returns the docs app shell. The API follows the OpenAI and Anthropic wire formats, which this checklist doesn't credit to a router, the same reading as RouterPlus (0 of 25). llms.txt and a Markdown copy of every page at the same path with `.md` (10). Pages say which endpoint to prefer and why, what isn't served (embeddings, files, batches), which Chat Completions controls return 501, and which workload suits which job (17 of 20). Router-only fields are tabled with types and bounds, the route selector rules are stated (`model` or `models` but never both, 1 to 15 candidates), over-limit timeouts are a 400 naming the maximum, and the model list documents a typed `router` object with a `schema_version`. Request bodies otherwise follow the upstream formats (12 of 15). curl, OpenAI SDK, Anthropic SDK, LangChain, Vercel AI SDK, LlamaIndex and Pydantic AI examples, and an error reference with a status, code and action for each case (15). Paths sit under `/v1` and the model object is versioned, but no API changelog or dated release notes were found (4 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### Maintenance \u0026 community: Vertex AI (Gemini Enterprise Agent Platform) +32\n\n- Router.com (Ramp Router) (59): Router, read on the model lines for a closed service. The Ramp CLI that ships the `router` commands tagged v0.2.91 on 3 November 2026, a release that changes `router.py` and `router_credentials.py`, one of 81 tags since 6 August (30). Models carry a `deprecated` status and the docs list deprecated and retired models, but no notice period is stated, and the Baseten retirement note gives no date and says requests aren't redirected (4 of 12). Provider-specific Baseten ids and several Fireworks models were retired without dates. The API host moved from router-api.ramp.com to api.router.com, and the old host still answers (3 of 8). No public API changelog. Support is a dashboard button and router@ramp.com, not tested (5 of 15). ramp-cli issue replies were not read, because GitHub's API wasn't available to this session (3 of 10). No API SDK. The Ramp CLI (MIT, npm @ramp/router and @ramp/cli, tagged v0.2.91 in the repository, Homebrew; npm itself not read) sets up agents and keys (7 of 15). The CLI repository has CI, build, npm and router-integration workflows and a tests folder, with 46 commit days since 29 July. ci.yml runs `cargo test` and `pytest` on pushes to main, and the results were not readable (7 of 10).\n- Vertex AI (Gemini Enterprise Agent Platform) (91): Model reading. Gemini Omni 1.2 Flash GA on 5 November, Grok 4.7 GA on 27 October, Gemini 4 Argon GA on 13 October and Claude Haiku 5.5 on 7 October 2026 (30). Stable models stay at least 12 months, and since 6 October Gemini 4 Argon and Gemini 3.8 Flash are in that tier, while 3.7 and 3.6 Flash remain short-term with at least 45 days' notice once a date is set (10 of 12, up from 8). Gemini 2.5 Pro, Flash and Flash-Lite were due to retire on 20 October, three models on one date after more than 12 months, with replacements named. We didn't check partner model retirements (6 of 8, down from 8). Dated release notes on most working days, newest 5 November, and Cloud Customer Care (15). python-genai replies not sampled this run (5 of 10). Current SDKs, google-genai 3.0.0 on 6 November and `@google/genai` 3.0.0, and google-cloud-aiplatform 2.7.0 on 28 October 2026 (15). Supported runtimes stated, Python 3.10 or later and Node 20 or later, per the 6 October check (10). Unchanged at 91.\n\n### Security \u0026 auth: Vertex AI (Gemini Enterprise Agent Platform) +31\n\n- Router.com (Ramp Router) (66): Router, read on the model lines. Router keys are shown once, can expire, carry lifetime or periodic spend caps, can be locked, unlocked or revoked, and each key has its own model set and default workload. No permission scopes or programmatic rotation were found (24 of 30). The docs FAQ says Ramp-side content recording is on by default and keeps inputs, outputs and tool calls for one year for debugging, semantic analysis and product improvement, with detected personal data removed before product use. Provider training terms are in Ramp's Provider Schedule, which renders only with JavaScript. Its 27 October reading came from the legal site's script and is no longer counted, so the line is held (6 of 20). Recording can be switched off account-wide, propagating asynchronously and without deleting existing archives, and flagged content may still be kept up to 30 days. The docs FAQ points to the Provider Schedule for zero data retention policies and exceptions, which could not be read, so the line is held (10 of 15). Logs show model, provider, status, tokens, cost, latency, fallback candidates, credential source and routing decisions per request, with usage export to S3 for Router Admins (14 of 15). A valid security.txt on router.com points to Ramp's security address. Ramp's SOC 2 and ISO 27001 reports, per the ramp listing's 8 October check, were not shown to cover Router, which is a separate product under its own terms. No bug bounty found (12 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### Transparency \u0026 trust: Vertex AI (Gemini Enterprise Agent Platform) +26\n\n- Router.com (Ramp Router) (64): Closed service. The Router Terms of Service, Router Privacy Notice and Provider Schedule render only with JavaScript. Their 27 October readings came from the legal site's script and are no longer counted, so the lines resting on them are held, as on ramp. The CLI is MIT (16 of 30). The docs FAQ states the one-year default recording, the opt-out and the PII step, and links Ramp's general privacy policy. Every link to the Router Privacy Notice answers 301 to that general policy (16 of 30). No deprecation policy found, and model retirements in the docs carry no dates (5 of 20). The docs FAQ names the providers whose infrastructure runs the models, says all models run on US infrastructure and points to the Provider Schedule for provider retention terms. No Router subprocessor list was found (13 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### Agent ergonomics: Vertex AI (Gemini Enterprise Agent Platform) +20\n\n- Router.com (Ramp Router) (77): Router, read on the model lines (tool use, structured output, caching, context, batch, SDKs, errors). Tools pass through on Responses, Messages and Chat Completions, and `GET /v1/models` reports `tools.supported` and `parallel` per model, with `null` where Router doesn't know. Behaviour depends on the model (16 of 20). The docs say JSON Schema output is expected to work across providers subject to model support, and each model carries a `structured_outputs` flag. A request the provider can't represent is a 501 (12 of 15). Cache read and write prices per model, a `prompt_cache_key` session lease of 5 or 30 minutes that keeps a session on the provider with a warm cache, and `cache_control` on Messages (14 of 15). Contexts up to 1,050,000 tokens on GPT-6.1 Sol and 1,048,576 on Kimi K3, a judgement call since a router has no default model (15). No batch route; the docs say Router doesn't serve batches (0 of 10). No SDK of its own. The OpenAI and Anthropic SDKs work with a changed base URL, framework setups are documented, and the MIT Ramp CLI configures six coding agents (5 of 10). Typed codes for every error, a `limit` object naming the cap and who set it, an all-candidates-failed summary, request and trace ids on every response and the serving provider in a header (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 | Router.com (Ramp Router) | Vertex AI (Gemini Enterprise Agent Platform) | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 22 | 99 | Vertex AI (Gemini Enterprise Agent Platform) +77 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 58 | 94 | Vertex AI (Gemini Enterprise Agent Platform) +36 |\n| Agent ergonomics | 13% (16.2 this run) | 77 | 97 | Vertex AI (Gemini Enterprise Agent Platform) +20 |\n| Security \u0026 auth | 14% (17.5 this run) | 66 | 97 | Vertex AI (Gemini Enterprise Agent Platform) +31 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 40 | 40 | even |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 59 | 91 | Vertex AI (Gemini Enterprise Agent Platform) +32 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 64 | 90 | Vertex AI (Gemini Enterprise Agent Platform) +26 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **53.7 · D** | **88.7 · AA** | |\n\n## Facts side by side\n\n| Fact | Router.com (Ramp Router) | Vertex AI (Gemini Enterprise Agent Platform) |\n| --- | --- | --- |\n| Kind | Model router | Model API |\n| Vendor | Ramp | Google Cloud |\n| Hosted endpoint | `https://api.router.com/v1` | `https://aiplatform.googleapis.com/v1` |\n| Transports | HTTP | HTTP |\n| Auth | API key | OAuth or key |\n| Pricing | Pay per use | Pay per use |\n| x402 | no | no |\n| Licence | Closed service under the Router Terms of Service (last updated 31 August 2026). The Ramp CLI that configures coding agents for Router is MIT. | 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 | 2026-11-03 | 2026-11-05 |\n| Terms last updated | couldn't be read | 2026-09-02 |\n| Privacy policy last updated | couldn't be read | 2026-10-01 |\n| Customer content may train models | couldn't be read | yes |\n| Terms restrict automated access | couldn't be read | not found in the text |\n| Terms restrict benchmarking | couldn't be read | not found in the text |\n| Terms or service can change without notice | couldn't be read | not found in the text |\n| Arbitration or class-action waiver | couldn't be read | not found in the text |\n| Popularity | 1.7k npm/wk | 20.9M PyPI/wk |\n\n## How the scores have moved\n\n### Router.com (Ramp Router)\n\n- -0.6 on 4 November 2026 (C to D): correction\n- -0.2 on 30 October 2026: checklist\n\n### Vertex AI (Gemini Enterprise Agent Platform)\n\nNo score change since it was listed.\n\n## Verdicts\n\n**Router.com (Ramp Router).** Detailed Markdown docs with typed error codes, per-model capability data and routing an agent can set per request. No OpenAPI document, status page, changelog or published rate limits were found. Signup needs a US business email in a browser, and Ramp records prompts and outputs for a year by default unless switched off.\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### Router.com (Ramp Router)\n\n1. Switch off content recording in Settings before sending private data. It is on by default and keeps prompts and outputs for a year\n2. Read model ids from `GET /v1/models` at runtime. Ids are account-specific, an unknown one is a 404, and Gemini ids need your own Google key\n3. Use `POST /v1/responses` with a `models` list for fallbacks. Router stops falling back once a stream has started\n4. Set `fallback_timeout` and `provider_timeout`, or `allow_flex_tier: false`, when latency matters. Flex routing is on by default\n5. Treat both `401 invalid_api_key` and `401 api_key_deactivated` as a possibly locked key, and stop retrying on `402`\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, Router.com (Ramp Router) or Vertex AI (Gemini Enterprise Agent Platform)?\n\nVertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against Router.com (Ramp Router)'s 53.7 (D), and leads in 6 of 7 scored categories.\n\n### Do Router.com (Ramp Router) and Vertex AI (Gemini Enterprise Agent Platform) need an API key?\n\nRouter.com (Ramp Router) needs an API key. Vertex AI (Gemini Enterprise Agent Platform) takes an API key or an OAuth sign-in.\n\n### Can an agent call Router.com (Ramp Router) and Vertex AI (Gemini Enterprise Agent Platform) without installing anything?\n\nYes. Router.com (Ramp Router) has a hosted endpoint at https://api.router.com/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/ramp-router-vs-vertex-ai.json, and with the fewest tokens: https://www.anchorterminal.com/compare/ramp-router-vs-vertex-ai.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"ramp-router\", \"b\": \"vertex-ai\"}`. From a terminal: `anchor compare ramp-router vertex-ai`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/ramp-router.json and https://www.anchorterminal.com/api/v1/tools/vertex-ai.json\n\n## Other comparisons with Router.com (Ramp Router) or Vertex AI (Gemini Enterprise Agent Platform)\n\n- [Amazon Bedrock vs Router.com (Ramp Router)](https://www.anchorterminal.com/compare/amazon-bedrock-vs-ramp-router.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 Router.com (Ramp Router)](https://www.anchorterminal.com/compare/anthropic-api-vs-ramp-router.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 Router.com (Ramp Router)](https://www.anchorterminal.com/compare/azure-openai-vs-ramp-router.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 Router.com (Ramp Router)](https://www.anchorterminal.com/compare/blockrun-ai-vs-ramp-router.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 Router.com (Ramp Router)](https://www.anchorterminal.com/compare/cerebras-inference-vs-ramp-router.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 Router.com (Ramp Router)](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-ramp-router.md)\n- [Cloudflare AI Gateway vs Vertex AI (Gemini Enterprise Agent 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[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 Router.com (Ramp Router)](https://www.anchorterminal.com/compare/antseed-vs-ramp-router.md)\n- [Eden AI vs Router.com (Ramp Router)](https://www.anchorterminal.com/compare/eden-ai-vs-ramp-router.md)\n- [Hugging Face Inference Providers vs Router.com (Ramp Router)](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-ramp-router.md)\n- [LiteLLM vs Router.com (Ramp Router)](https://www.anchorterminal.com/compare/litellm-vs-ramp-router.md)\n- [Router.com (Ramp Router) vs RouterPlus](https://www.anchorterminal.com/compare/ramp-router-vs-routerplus.md)\n- [Router.com (Ramp Router) vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/ramp-router-vs-tencent-tokenhub.md)\n- [Router.com (Ramp Router) vs Vercel AI Gateway](https://www.anchorterminal.com/compare/ramp-router-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": "Router.com (Ramp Router) vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "" } ], "description": "Vertex AI scores 88.7 (AA) to Router.com's 53.7 (D) for llm inference. 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