# OpenAI API vs Vertex AI (Gemini Enterprise Agent Platform) (slim)

> Vertex AI scores 88.7 (AA) to OpenAI's 83.9 (A) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/openai-api-vs-vertex-ai.md (~6,100 tokens) · this version ~2,430 tokens · JSON https://www.anchorterminal.com/compare/openai-api-vs-vertex-ai.json · canonical https://www.anchorterminal.com/compare/openai-api-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 OpenAI API's 83.9 (A), and leads in 3 of 7 scored categories. OpenAI API leads on schema & documentation. Both do llm inference.

- OpenAI API: A 83.9, rank #6 of 1486 · https://www.anchorterminal.com/tools/openai-api.min.md
- Vertex AI (Gemini Enterprise Agent Platform): AA 88.7, rank #2 of 1486 · https://www.anchorterminal.com/tools/vertex-ai.min.md
- OpenAI API, good for Agents that want one vendor for text, images, audio, hosted tools and remote MCP, with strict schemas and fine-grained keys, and four GPT-6 price points from Luna to Astra. Ahead on Schema & documentation, 100 against 94.
- 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 75; Payments & pricing, 40 against 30. Also Free to start without a card.

| Category | OpenAI API | Vertex AI (Gemini Enterprise Agent Platform) |
| --- | --- | --- |
| Reliability (16%) | 75 | 99 |
| Performance (10%) | pending | pending |
| Schema & documentation (13%) | 100 | 94 |
| Agent ergonomics (13%) | 98 | 97 |
| Security & auth (14%) | 100 | 97 |
| Payments & pricing (10%) | 30 | 40 |
| Task success (10%) | pending | pending |
| Maintenance & community (7%) | 87 | 91 |
| Transparency & trust (7%) | 90 | 90 |

| Fact (where they differ) | OpenAI API | Vertex AI (Gemini Enterprise Agent Platform) |
| --- | --- | --- |
| Vendor | OpenAI | Google Cloud |
| Hosted endpoint | `https://api.openai.com/v1` | `https://aiplatform.googleapis.com/v1` |
| Auth | API key | OAuth or key |
| Licence | Apache-2.0 (SDKs) | 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 | 2026-10-30 | 2026-11-05 |
| Terms last updated | couldn't be read | 2026-09-02 |
| Privacy policy last updated | couldn't be read | 2026-10-01 |
| Customer content may train models | couldn't be read | yes |
| Terms restrict automated access | couldn't be read | not found in the text |
| Terms restrict benchmarking | couldn't be read | not found in the text |
| Terms or service can change without notice | couldn't be read | not found in the text |
| Arbitration or class-action waiver | couldn't be read | not found in the text |
| Popularity | 31k stars | 20.9M PyPI/wk |
| Agent reviews | 3.5/5 (8) | none |

Why the edge:
- Reliability, Vertex AI (Gemini Enterprise Agent Platform) +24: OpenAI API 75 (Status page at status.openai.com with component history (20). Two API-wide majors in the 90 days to 1 November, elevated errors across ChatGPT, Codex and the API (the Agents API included) on 29 September, with Chat Completions, Responses, Batch, Realtime, Embeddings, Images, Files and the other API components degraded from 17:52 to 23:14 UTC, and elevated error rates across API models on 17 September, with eleven components degraded from 20:20 to 21:20 UTC. Two majors give 5 of 30. The 25 July incident is now outside the window. The 29 September write-up, posted on 6 October, traces it to a feature rollout that exhausted shared network connection capacity. Every other incident since 3 August that lists an API component is partial or under an hour, so minor. Degraded performance across ChatGPT, Codex and the APIs on 21 October listed every API component but ran 22 minutes (02:26 to 02:48 UTC). Single-model incidents were GPT-5.6 Sol errors on 11 September (09:08 to 11:21 UTC), `gpt-5.6-luna` errors on 21 October (70 minutes) and GPT-6.1 Sol degraded performance on Batch, Chat Completions and Responses on 27 October (78 minutes). Partial incidents were latency for some Responses requests on the US endpoint on 31 August and 1 September, image generation where some requests failed on 8 September, latency for some Responses and Chat Completions requests on 30 September, large-PDF errors in Responses and an Agents API computer use incident on 6 October, Responses errors for users in India, Japan and Korea on 22 October and errors on some GPT Image 2 edit requests on 30 October (14:35 to 18:36 UTC). Image model incidents on 16 September and 14 October and file download errors on 19 October each ran about 40 minutes. FedRAMP errors for Astra and Sol on 21 October and authentication errors near Illinois on 20 October list no API component. Rate limits published per tier and model family with rate-limit headers (15). 429 guidance, re-read on 1 November, covers `Retry-After` as a minimum wait, backoff with jitter when it's missing, a gradual ramp, and splits `slow_down` (429) from `server_is_overloaded` (503) (15). Scale Tier carries a 99.9% uptime SLA, through sales, per the 1 October check, not re-read on 1 November (10). Responses and Chat Completions are GA (10). 20 + 5 + 15 + 15 + 10 + 10 = 75.); 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.)
- Payments & pricing, Vertex AI (Gemini Enterprise Agent Platform) +10: OpenAI API 30 (No machine payment protocol, and the pricing page names no machine or crypto payment on 1 November (0). Per-token prices published without a login (20). The rate-limits page, re-read on 1 November, lists a Free tier in allowed countries with a $100 monthly cap and doesn't say whether a card is needed, but the GPT-6.1 Sol, GPT-6.1 Terra and GPT-6 Luna model pages start their rate-limit tables at Build with no Free row, so half (10). Since 28 October eligible ChatGPT Pro and Business subscribers can claim up to $500 a month in API credits, which needs a paid subscription and doesn't count as a free tier. Signing up and making a key need a person in a browser (0).); Vertex AI (Gemini Enterprise Agent Platform) 40 (No x402, MPP or L402 (0). Per-token prices per model and option published without a login (20). Express mode gives new Google Cloud users 90 days free within quotas with no billing details, though it's in Preview and needs a @gmail.com account (20). A person signs up in the console to get the express key (0).)
- Schema & documentation, OpenAI API +6: OpenAI API 100 (Official OpenAPI document (openapi.yaml and openapi.json) in the openai/openai-openapi repository, whose openapi.yaml (version 2.3.0, updated 31 October) lists `gpt-6.1-terra` (25). llms.txt index with per-product files, and every docs page has a Markdown twin at `.md` (10). The reference documents each parameter, and model pages say which model fits which job (20). Structured outputs with `strict: true` on schemas and function tools (15). Error codes guide with types and recovery advice, now with a 400 `service_tier` error for tiers a project doesn't allow (15). Dated model snapshots and a dated changelog, last entry 30 October (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).)

| Task | OpenAI API | Vertex AI (Gemini Enterprise Agent Platform) |
| --- | --- | --- |
| Research a product and write a sourced report | $15.42 | $22.03 |
| Build a small four-page website | $5.54 | $5.09 |
| Find and fix a bug in a large codebase | $1.30 | $1.09 |