# RouterPlus vs Vertex AI (Gemini Enterprise Agent Platform) (slim)

> Vertex AI scores 88.7 (AA) to RouterPlus's 50.3 (D) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/routerplus-vs-vertex-ai.md (~8,050 tokens) · this version ~4,280 tokens · JSON https://www.anchorterminal.com/compare/routerplus-vs-vertex-ai.json · canonical https://www.anchorterminal.com/compare/routerplus-vs-vertex-ai
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-07
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Vertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against RouterPlus's 50.3 (D), and leads in 6 of 7 scored categories. Both do llm inference.

- RouterPlus: D 50.3, rank #1071 of 1510 · https://www.anchorterminal.com/tools/routerplus.min.md
- Vertex AI (Gemini Enterprise Agent Platform): AA 88.7, rank #2 of 1510 · https://www.anchorterminal.com/tools/vertex-ai.min.md
- RouterPlus, good for Teams that call Claude, GPT and open-weight models from one key and want the cost of every call in the response, with their own provider keys where they have them.
- Vertex AI (Gemini Enterprise Agent Platform), good for Google Cloud customers who need Gemini with residency, VPC-SC, provisioned throughput and an SLA, or Claude under a Google bill. Ahead on Reliability, 99 against 42; Schema & documentation, 94 against 59; Agent ergonomics, 97 against 71; Security & auth, 97 against 59; Maintenance & community, 91 against 44; Transparency & trust, 90 against 41. Also Agent-ready, a grade of BB or better; Free to start without a card.

| Category | RouterPlus | Vertex AI (Gemini Enterprise Agent Platform) |
| --- | --- | --- |
| Reliability (16%) | 42 | 99 |
| Performance (10%) | pending | pending |
| Schema & documentation (13%) | 59 | 94 |
| Agent ergonomics (13%) | 71 | 97 |
| Security & auth (14%) | 59 | 97 |
| Payments & pricing (10%) | 40 | 40 |
| Task success (10%) | pending | pending |
| Maintenance & community (7%) | 44 | 91 |
| Transparency & trust (7%) | 41 | 90 |

| Fact (where they differ) | RouterPlus | Vertex AI (Gemini Enterprise Agent Platform) |
| --- | --- | --- |
| Kind | Model router | Model API |
| Vendor | RouterPlus | Google Cloud |
| Hosted endpoint | `https://api.routerplus.com/v1` | `https://aiplatform.googleapis.com/v1` |
| Auth | API key | OAuth or key |
| Licence | Closed service. No terms of service for the gateway were found on routerplus.com or app.routerplus.com on 13 October 2026. The only terms on the site govern the capacity request form and name EVO HQ Inc, a Delaware corporation (https://routerplus.com/capacity/terms/). | Proprietary service under the Google Cloud Platform terms. Partner models carry their providers' terms. The Google Gen AI SDKs are Apache-2.0 |
| llms.txt | yes | no |
| Last release | none | 2026-11-05 |
| Terms last updated | no document linked | 2026-09-02 |
| Privacy policy last updated | no document linked | 2026-10-01 |
| Customer content may train models | not read yet | yes |
| Terms restrict automated access | not read yet | not found in the text |
| Terms restrict benchmarking | not read yet | not found in the text |
| Terms or service can change without notice | not read yet | not found in the text |
| Arbitration or class-action waiver | not read yet | not found in the text |
| Popularity | none | 20.9M PyPI/wk |

Why the edge:
- Reliability, Vertex AI (Gemini Enterprise Agent Platform) +57: RouterPlus 42 (Hosted reading. No status page found. Model pages show each provider's uptime over the last 24 hours and no incident history, and status.routerplus.com failed at our proxy again on 4 November 2026 (0). No readable incident history (5). The limits page, re-read on 4 November 2026, gives 20 requests a minute until the organisation's first purchase, then 300 per console key and 60 for the managed Playground key, with token-per-minute and in-flight limits per organisation and key (15). Rate-limit 429s carry `retry-after` from 1 to 59 seconds and `metadata.retry_at`, the errors page gives a retry or no-retry rule for each error class, and the docs say a retry is a new billed request because there is no idempotency key. That is safe-retry guidance without keys on the billed call, the value this run settled for routers such as ramp-router (12, 15 before). The homepage says "Production-grade SLAs", but no SLA terms were found, and the only terms on the site say a stated response time is not a service level (0). The chat and messages surfaces carry no beta label. The Responses API is a preview for non-OpenAI models and Optimize is paused, neither of which is the main surface (10). 0 + 5 + 15 + 12 + 0 + 10 = 42.); 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.)
- Transparency & trust, Vertex AI (Gemini Enterprise Agent Platform) +49: RouterPlus 41 (Closed service with no terms of service found. The only terms on the site govern the capacity request form, under EVO HQ Inc (0 of 30). The data policy page is detailed, lists what is stored and why, and gives a 30-day period for request logs and each provider's retention flag. Its 4 November 2026 text, which logs request content by default, no longer agrees with the homepage FAQ; that contradiction is charged once as a misleading claim under negative events, not on this line. There is no privacy policy, no DPA and no retention period for account data such as email addresses (14 of 30, held). Model retirement by `deprecation_date` is documented with no notice period, and no dated deprecation notices were found (4 of 20). The docs name Clerk, Resend and an AWS bucket, and say RouterPlus's own GPUs run in the United States. The form's terms name Supabase, Cloudflare and Resend. No complete subprocessor list or gateway hosting location was found (8 of 20).); 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).)
- Maintenance & community, Vertex AI (Gemini Enterprise Agent Platform) +47: RouterPlus 44 (Router, read on the model lines. No changelog or release notes found. The blog, re-read on 4 November 2026, dates the launch of ScaleDown's extract-1 and summarize-1 on chat completions and classify-1 on the decisions API to 13 October 2026, and the catalogue now lists 105 chat models against 19 on 13 October, so the API changed within the last 30 days (30). The docs also date a console change on 17 October 2026 (keys can be copied again), which isn't counted, since it changes the console and not the API. Models carry a `deprecation_date` that delists them automatically, with no notice period stated (3 of 12). `POST /v1/signup` and the magic-link route were removed and Optimize is paused, none with a date we could find (3 of 8). No public changelog. Support is reached through the console and an email address, and wasn't tested (3 of 15). No public issue tracker for the gateway (0 of 10). No official SDK. The docs rely on the OpenAI and Anthropic SDKs and give client setups (5 of 15). No package or public repository to check (0 of 10).); 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.)
- Security & auth, Vertex AI (Gemini Enterprise Agent Platform) +38: RouterPlus 59 (Router, read on the model lines. `tm_vk_` keys are stored as SHA-256 hashes and revocable, each bound to a workspace and principal, with per-key RPM and monthly spend caps. Since 17 October 2026 the console also keeps an encrypted copy so an owner or admin can copy a key again, and an organisation can ask for copying to be turned off. Inference keys have no management rights. There are no permission scopes on a key and no SSO or SCIM (24 of 30). RouterPlus says it does not train on request logs and does not share them, and deletes them after 30 days. Most Claude and GPT routes are marked `prompt_logging: retained` with no ZDR, so retention and training upstream rest on each provider's API terms, while DeepInfra's open models, Perplexity, Cloudflare Workers AI, Fastino and RouterPlus's own models declare `none` (12 of 20, held). The data policy re-read on 4 November 2026 says requests and responses to non-dedicated endpoints are now logged by default for up to 30 days for debugging, with recognised keys removed. On 13 October it said content was kept only for hackathon accounts. Opting out takes a request to support, dedicated endpoints are excluded, and the `zdr` and `data_collection: deny` filters still remove every marketplace route, so they work only on the caller's own provider keys. Cloudflare AI Gateway, with default logging and a per-request header to switch it off, has 11 here (7 of 15, 10 before). `GET /v1/generation` lists every attempt behind a request with provider, tokens and cost, and the console has usage and logs (14 of 15). No security.txt (404 on both hosts on 4 November 2026), disclosure policy, bug bounty or certification found. The footer's Security link is an email to founders@evo-hq.com (2 of 20). 24 + 12 + 7 + 14 + 2 = 59.); 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).)
- Schema & documentation, Vertex AI (Gemini Enterprise Agent Platform) +35: RouterPlus 59 (Router, scored on the API lines. No OpenAPI or other machine-readable contract for the gateway was found. It follows the OpenAI and Anthropic wire formats, which this checklist doesn't credit to a reseller, the same reading as Antseed (0 of 25). llms.txt, llms-full.txt and a Markdown copy of every page (10). Each route page says what it is for, what isn't available, and which route to use for which model, and the agent integration guide lists what not to build on (18 of 20). Request fields follow the upstream formats, and the wire compatibility page tables which fields pass, translate, drop or fail with a typed 400 (12 of 15). Curl, Python and TypeScript examples on every page, and an error reference with a class, status and remedy for each error (15). Routes are versioned under /v1 and the wire compatibility page says changing it needs a recorded decision, but no changelog or dated release notes were found, re-read on 4 November 2026 (4 of 15).); 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).)
- Agent ergonomics, Vertex AI (Gemini Enterprise Agent Platform) +26: RouterPlus 71 (Router, read on the model lines (tool use, structured output, caching, context, batch, SDKs, errors). Tools pass through on both surfaces, and Anthropic server tools such as web search work for Claude models on `/v1/messages`. Behaviour depends on the model (15 of 20). `response_format` works for GPT ids and the open models (re-read on 4 November 2026), and the docs tell callers to get JSON from Claude through a single tool, so structured output still rests on the provider (8 of 15, held). Cached-input and cache-write prices per model, a session id that keeps provider caches warm, and `cache_control` on the Anthropic surface (13 of 15). The catalogue's largest contexts are 1,050,000 tokens on GPT-6.1 Sol and 1,000,000 on Claude Sonnet 5.5, a judgement call since a router has no default model (15). No batch route (0 of 10). No SDK of its own. The OpenAI and Anthropic SDKs work with a changed base URL, and the docs give setups for ten coding tools (5 of 10). A stable `error_type` in every body and header, an origin header, the limit that refused a request, and `x-tm-dropped-params` naming every dropped field (15).); 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).)