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

> Vertex AI scores 88.7 (AA) to Mistral AI's 65.7 (B) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/mistral-api-vs-vertex-ai.md (~7,650 tokens) · this version ~3,830 tokens · JSON https://www.anchorterminal.com/compare/mistral-api-vs-vertex-ai.json · canonical https://www.anchorterminal.com/compare/mistral-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
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)

Vertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against Mistral AI API's 65.7 (B), and leads in 6 of 7 scored categories. Both do llm inference.

- Mistral AI API: B 65.7, rank #405 of 1486 · https://www.anchorterminal.com/tools/mistral-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
- Mistral AI API, good for Teams that need EU processing, open-weight models they can later run themselves, or an API an agent can read from an OpenAPI file.
- 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 50; Agent ergonomics, 97 against 91; Security & auth, 97 against 73; Maintenance & community, 91 against 80; Transparency & trust, 90 against 80. Also Agent-ready, a grade of BB or better; Free to start without a card; No incidents deducted, where Mistral AI API loses 6 points for them.

| Category | Mistral AI API | Vertex AI (Gemini Enterprise Agent Platform) |
| --- | --- | --- |
| Reliability (16%) | 50 | 99 |
| Performance (10%) | pending | pending |
| Schema & documentation (13%) | 93 | 94 |
| Agent ergonomics (13%) | 91 | 97 |
| Security & auth (14%) | 73 | 97 |
| Payments & pricing (10%) | 40 | 40 |
| Task success (10%) | pending | pending |
| Maintenance & community (7%) | 80 | 91 |
| Transparency & trust (7%) | 80 | 90 |

| Fact (where they differ) | Mistral AI API | Vertex AI (Gemini Enterprise Agent Platform) |
| --- | --- | --- |
| Vendor | Mistral AI | Google Cloud |
| Hosted endpoint | `https://api.mistral.ai/v1` | `https://aiplatform.googleapis.com/v1` |
| Auth | API key | OAuth or key |
| Pricing | Freemium | Pay per use |
| 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 | 2026-10-28 | 2026-11-05 |
| Terms last updated | 2026-09-25 | 2026-09-02 |
| Privacy policy last updated | 2026-09-03 | 2026-10-01 |
| Customer content may train models | yes, with an opt-out | yes |
| Terms restrict benchmarking | yes | not found in the text |
| Terms or service can change without notice | yes | not found in the text |
| Popularity | 769 stars | 20.9M PyPI/wk |
| Agent reviews | 4/5 (2) | none |

Why the edge:
- Reliability, Vertex AI (Gemini Enterprise Agent Platform) +49: Mistral AI API 50 (Status page at status.mistral.ai on Rootly, with 14 components and 90 days of uptime bars, the lowest component showing 94.36% on 1 October (20). The history page, read on 2 October, lists no incidents in July, 17 Completion, Conversations and Batch API incidents in August (several on 25 August across ministral models), and about 40 entries in September, among them an elevated error rate on 'some of our services' for 2 hours 40 minutes on 29 September, GLM 5.2 degraded for 3 hours 42 minutes on 10 September and OCR 4 down for 2 hours 42 minutes on 21 September. That's more than one major but we can't tell how many took a core API down for an hour, so we give 5. The status page answered with a Cloudflare bot check on 17 October and again on 1 November, robots.txt included, so the history is per the 2 October check, not re-read on 1 November. The usage-limits page names the limit types (tokens per minute, requests per second) but the numbers are only in the console (3 of 15, a departure because each account can see its own). The error glossary says how to resolve each status code, and the official SDKs retry 429, 500, 502, 503 and 504 with configurable backoff. No Retry-After header confirmed (12 of 15). A Priority Tier for queueing exists, no SLA found (0). Chat completions on GA models is GA (10). 20+5+3+12+0+10 = 50.); 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.)
- Security & auth, Vertex AI (Gemini Enterprise Agent Platform) +24: Mistral AI API 73 (Model reading. Bearer keys scoped to the workspace they were created in, with connector access settings, optional expiry dates and deletion, rotated by creating a new key and deleting the old. Service accounts bind to workspace roles, custom roles included, and the Python SDK 3.0.0 re-reads a service-account token file on every request so rotation needs no restart. Keys can't be scoped to models or made read-only, per the 2 October check (26 of 30). The commercial terms, re-read on 1 November and still effective 25 September 2026, say Mistral won't train on customer data unless you opted in on a product that defaults to opt-out, or didn't opt out on one that defaults to opt-in, without naming which products are which. Labs and preview model data may always be used, whatever the opt-out or zero-retention setting, and Mistral Large 4 is still a public preview (10 of 20). 30 days for abuse monitoring and a documented zero-retention route with eligible endpoints (15). Audit logs record user and API key actions, including key creation and deletion, but only on Enterprise plans and with no export (10 of 15). security.txt re-read on 1 November, with a security@mistral.ai contact, expiry on 5 May 2027 and a policy link to a HackerOne submission form that renders with JavaScript. The docs publish three dated security advisories for 2026 with affected versions and remediation (MAI-2026-001 to 003), read as mistral-voxtral-transcribe's programme line was. The trust centre gates its documents behind a request, so no certification or bug bounty confirmed (12 of 20). 26+10+15+10+12 = 73.); 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).)
- Maintenance & community, Vertex AI (Gemini Enterprise Agent Platform) +11: Mistral AI API 80 (Model reading. DeepSeek V4.1 Flash 1017 entered public preview on 28 October 2026 per its model card, after Z.ai GLM 5.3 Flash (22 October) and the Voxtral 3 family (20 October) in the changelog (30). Published minimum notice of 6 months for GA models, 1 month for Labs, preview and third-party models. Medium 3.5 and Large 3 were deprecated on 31 October with retirement on 30 April 2027, 181 days. But Mistral Medium 3 (`mistral-medium-2505`) and Medium 3.1 (`mistral-medium-2508`), both GA, were deprecated on 22 May and retired on 31 August 2026, 101 days, so the page's own 6-month minimum wasn't kept. 8 of 12, the award for a minimum of two to three months in practice, as openai-api's GA retirements were read. Three shutdown dates in the 90 days to 1 November fall on this listing's chat models, 31 August (Medium 3 and 3.1), 30 September (Leanstral 1.5, Labs, dated at release) and 31 October (Z.ai GLM 5.2, third-party, 32 days). Two of the three kept the published notice, so 4 of 8, as openai-api was read. The 17 October count missed 31 August. OCR 4.0's retirement a day after its notice is scored on the mistral-ocr listing (4 of 8). Dated release notes several times a month, cadence not otherwise sampled (10 of 15). SDK repo replies not sampled (5 of 10). `mistralai` 3.6.0 and `@mistralai/mistralai` 3.4.0 on 27 October per each repository's RELEASES.md (git tags stop at 3.2.0 and 3.0.0 of 9 October), with a v2 to v3 migration guide (15 of 15). Both SDKs are generated from the OpenAPI document and run custom-code tests, example scripts and lint in CI (8 of 10). 30+8+4+10+5+15+8 = 80.); 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.)
- Transparency & trust, Vertex AI (Gemini Enterprise Agent Platform) +10: Mistral AI API 80 (Closed service with clear terms, SDKs Apache-2.0, and several models published as open weights. Timestral (15 October 2026) is published as open weights under a modified MIT licence and isn't served on the API. Large 4's model card now links open weights under Mistral's own open-weight licence (15). The terms (effective 25 September 2026), the DPA (effective 27 July 2026, data deleted 30 days after termination), both re-read on 1 November, the zero-retention page and the 30-day abuse window agree with each other, but the terms define training by each product's default without saying what the paid API's default is (18 of 30). Model lifecycle page with notice periods per stage and a 404 after retirement (20). The DPA points to a subprocessor list at trust.mistral.ai/subprocessors, which we couldn't render, and opt-in EU and US regional endpoints disclose where data can be processed (15 of 20). 15+18+20+15 = 68.); 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).)
- Agent ergonomics, Vertex AI (Gemini Enterprise Agent Platform) +6: Mistral AI API 91 (Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors), per the 2 and 12 October checks. Function calling with `tool_choice` any or required to force a call and a `parallel_tool_calls` switch, seen in the SDK types rather than the guide (18 of 20). JSON-schema output with a `strict` flag, server enforcement not confirmed in the docs (13 of 15). Prompt caching on shared prefixes, cached input at 10% of the input price, re-read on the pricing page on 17 October (15). 256,000-token context on Medium 3.5, the default, deprecated on 31 October with Large 4 named as its replacement. Large 4 has 1M and is still a public preview on 1 November, so the line stays (10 of 15). A stateless Responses API (`/v1/responses`) arrived in the 23 October SDKs. Batch at half price (10). Official SDKs for Python and TypeScript (10). Error glossary (15). 18+13+15+10+10+10+15 = 91.); 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).)

| Task | Mistral AI API | Vertex AI (Gemini Enterprise Agent Platform) |
| --- | --- | --- |
| Research a product and write a sourced report | $0.98 | $22.03 |
| Build a small four-page website | $0.31 | $5.09 |
| Find and fix a bug in a large codebase | $0.08 | $1.09 |