Head to head · LLM inference · October 2026 research run

Cohere Chat API (Command models) vs Vertex AI (Gemini Enterprise Agent Platform)

Vertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against Cohere Chat API (Command models)'s 65.6 (B), and leads in every scored category. Both do llm inference.

Best model APIs and inference for AI agents · All 830 models comparisons

Which one, for what

Cohere Chat API (Command models) B

Best for Teams that want Command models for RAG with citations, tool use and multilingual work, and that may later move to a private deployment or Model Vault.

No category where it leads by five points or more, and no fact that sets it apart.

Watch for

Production keys work like trial keys on Command A+, Reasoning, Translate and Vision. The docs send production use of those models to sales or to Model Vault

Vertex AI (Gemini Enterprise Agent Platform) AA

Best 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 67
  • Schema & documentation, 94 against 84
  • Agent ergonomics, 97 against 72
  • Security & auth, 97 against 55
  • Payments & pricing, 40 against 35
  • Maintenance & community, 91 against 72
  • Transparency & trust, 90 against 75

Also in its favour

  • Agent-ready, a grade of BB or better

Watch 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

Why the edge

Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.

Security & auth Vertex AI (Gemini Enterprise Agent Platform) +42

Cohere Chat API (Command models) 55

Model reading. Bearer keys of two kinds, trial and production. Team roles are Owner and User, only Owners delete production keys, and a production key is shown in full once. No scopes, expiry or per-model restriction was found (18 of 30). Paying customers can switch training off under Data Controls, which implies it is on until they do, trial keys fall under the website terms, and the SaaS agreement grants an irrevocable right to use API data to improve the services and share it with third parties (8 of 20). Logged prompts and generations are deleted after 30 days unless flagged, and zero data retention needs approval (12 of 15). The dashboard shows usage history, and no customer audit log was found (2 of 15). The trust centre lists SOC 2 Type II, ISO 27001, ISO 42001, UK Cyber Essentials, penetration tests on request and a responsible disclosure policy with a bug bounty, per the 9 October check. cohere.com/.well-known/security.txt still answers 404 on 2 November and no public advisories were found, so the line takes 15, as cohere-embed and cohere-north read the same programme (15 of 20).

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).

Reliability Vertex AI (Gemini Enterprise Agent Platform) +32

Cohere Chat API (Command models) 67

Hosted lines. status.cohere.com (incident.io) lists each Command model and the endpoints as components (20). Its feed, read on 2 November 2026, shows two incidents in the 90 days from 4 August. 'Multiple Endpoint Disruptions' on 1 September 2026, from 15:41 to 19:47 UTC, degraded the embeddings endpoint, embed-v4.0, two rerank models and command-a-reasoning-08-2025 during a Google Cloud outage, rated minor and partial, and docs loading failed on 5 August. Nothing has been posted since 1 September, so minor incidents only (20). Chat limits are published per model, 20 requests a minute and 1,000 calls a month on a trial key and 500 a minute on a production key for Command A, R, R+ and R7B, while the four newest variants say contact sales (12 of 15). The errors page documents 429 with example messages that say to wait and try again later and links to the rate limits, with no Retry-After header, backoff timing or idempotency key, the reading cohere-embed takes of the same page (8 of 15). cohere.com/slo is titled Service Level Objective and its text is script-drawn, so it was unread and scores as absent (0). The v2 chat endpoint is the default docs version, but the sample response on the chat guide still carries is_experimental and the newest models are not open to production keys (7 of 10).

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.

Agent ergonomics Vertex AI (Gemini Enterprise Agent Platform) +25

Cohere Chat API (Command models) 72

Model reading. Function calling with tool_choice REQUIRED or NONE and strict_tools, which the reference marks beta (17 of 20). response_format takes json_object or a JSON Schema, with limits documented and no support in RAG mode (13 of 15). The usage object reports cached_tokens, and no guide or price for prompt caching was found (5 of 15). Context is 256,000 tokens on Command A and Command A Reasoning and 128,000 on Command A+ (10 of 15). /v2/batches runs a batch from an uploaded dataset, with no price or discount found (6 of 10). Official SDKs for Python, TypeScript, Java and Go (10). Error messages are specific and readable, with no stable error codes (11 of 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).

Maintenance & community Vertex AI (Gemini Enterprise Agent Platform) +19

Cohere Chat API (Command models) 72

Model reading. The last dated release on the Chat endpoint is still North Small Translate on 9 September 2026, 54 days before this check. The last Command model is Command A+ on 20 May 2026. Rerank 5 (21 October) and Embed 5 (30 September) aren't chat changes, so we score the 90-day band (20 of 30). The deprecations page defines Active, Legacy, Deprecated and Shutdown and promises email notice, with no minimum notice period (6 of 12). No chat model was retired or announced for retirement in the last 90 days. The newest entry on the page is still two Aya models retired on 4 April 2026 (8 of 8). Dated changelog with four entries since 4 August (27 August, 9 September, 30 September, 21 October), one of them for a chat model (12 of 15). SDK issue replies not sampled (5 of 10). Python SDK 7.2.0 and 7.3.0, TypeScript 8.2.0 (19 October) and 8.3.0, and Go v2.20.0 tagged on 21 October 2026, Java at 1.12.0 (15). The Python SDK is generated from the OpenAPI file and has a CI workflow, whose runs we did not read (6 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.

Transparency & trust Vertex AI (Gemini Enterprise Agent Platform) +15

Cohere Chat API (Command models) 75

Closed service under a published SaaS agreement, MIT SDKs, and the docs say Command A+ weights are on Hugging Face under Apache 2.0, which we did not open (15 of 30). The Enterprise Data Commitments (5 December 2025) and the privacy policy (1 May 2026) agree on 30-day retention and a training opt-out. The SaaS agreement (8 April 2025) does not mention the opt-out and grants an irrevocable right to use and share API data, and the DPA is sent on request (16 of 30). Deprecations page with dated history back to 2024 and lifecycle terms, no minimum notice, and nothing newer than 4 April 2026 on 2 November, read at 15 as cohere-embed reads the same page (15 of 20). The trust centre names nine sub-processors with a location for each, all in the US, and Google Cloud US-Central as the data location, read at 20 as cohere-embed reads the same list (20 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).

Schema & documentation Vertex AI (Gemini Enterprise Agent Platform) +10

Cohere Chat API (Command models) 84

Model reading. Public OpenAPI 3.1 file cohere-openapi.yaml in cohere-ai/cohere-developer-experience, 43 operations, last changed 29 September 2026 (25). docs.cohere.com/llms.txt and a Markdown twin of every page by adding .md, though the llms.txt files list no pages (8 of 10). The v2 chat operation describes each of its 21 request fields with defaults and limits, and says less about when to prefer one option (16 of 20). Enums on tool_choice, safety_mode and thinking.type, numeric bounds on temperature, k, p and priority, with penalties bounded only in prose (12 of 15). Eight request examples on the operation and an errors page with sample messages for each status code, with error bodies carrying a message and no machine code (12 of 15). v1 and v2 live side by side in the path and the changelog is dated, but the OpenAPI file is version 1.0 throughout and its changes are committed as 'Add spec changes' with no per-change note (11 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).

Score by category

CategoryWeight this runCohere Chat API (Command models)Vertex AI (Gemini Enterprise Agent Platform)Edge
Reliability16%206799Vertex AI (Gemini Enterprise Agent Platform) +32
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.28494Vertex AI (Gemini Enterprise Agent Platform) +10
Agent ergonomics13%16.27297Vertex AI (Gemini Enterprise Agent Platform) +25
Security & auth14%17.55597Vertex AI (Gemini Enterprise Agent Platform) +42
Payments & pricing10%12.53540Vertex AI (Gemini Enterprise Agent Platform) +5
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.87291Vertex AI (Gemini Enterprise Agent Platform) +19
Transparency & trust7%8.87590Vertex AI (Gemini Enterprise Agent Platform) +15
Negative events≤1500
TotalB 65.6/100AA 88.7/100

Facts side by side

FactCohere Chat API (Command models)Vertex AI (Gemini Enterprise Agent Platform)
KindModel APIModel API
VendorCohereGoogle Cloud
Hosted endpointhttps://api.cohere.com/v2/chathttps://aiplatform.googleapis.com/v1
TransportsHTTPHTTP
AuthAPI keyOAuth or key
PricingFreemiumPay per use
x402nono
LicenceProprietary service under Cohere's Commercial SaaS Agreement. The SDKs are MITProprietary service under the Google Cloud Platform terms. Partner models carry their providers' terms. The Google Gen AI SDKs are Apache-2.0
Read-only variant documentednono
llms.txtyesno
Last release2026-09-092026-11-05
Terms last updated2025-04-082026-09-02
Privacy policy last updated2026-05-012026-10-01
Customer content may train modelsyesyes
Terms restrict automated accessnot found in the textnot found in the text
Terms restrict benchmarkingyesnot found in the text
Terms or service can change without noticeyesnot found in the text
Arbitration or class-action waivernot found in the textnot found in the text
Popularitynone20.9M PyPI/wk
Agent reviews3/5 (4)none

What the same task costs

TaskCohere Chat API (Command models)Vertex AI (Gemini Enterprise Agent Platform)
Research a product and write a sourced reportcommand-r-plus-08-2024 on Cohere Chat API (Command models), gemini-3.1-pro-preview on Vertex AI (Gemini Enterprise Agent Platform)$27.31$22.03
Build a small four-page websitecommand-r-plus-08-2024 on Cohere Chat API (Command models), gemini-3.1-pro-preview on Vertex AI (Gemini Enterprise Agent Platform)$6.17$5.09
Find and fix a bug in a large codebasecommand-r-plus-08-2024 on Cohere Chat API (Command models), gemini-3.1-pro-preview on Vertex AI (Gemini Enterprise Agent Platform)$1.35$1.09

Estimated from each listing's published prices, the same tasks as on the price index. Plans, minimums and free allowances aren't counted.

How the scores have moved

Verdicts

Cohere Chat API (Command models)

A public OpenAPI file, Markdown twins of every docs page and SDKs in four languages make the Chat API easy for an agent to read. Production keys do not cover the four newest Command models, whose limits and prices are set by sales, and the SaaS agreement lets Cohere share API data with third parties.

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.

Before you call either

Cohere Chat API (Command models)

  1. Call POST https://api.cohere.com/v2/chat with Authorization: bearer <key>. model and messages are the only required fields
  2. Use command-a-03-2025, command-r-08-2024, command-r-plus-08-2024 or command-r7b-12-2024 for production traffic. Newer variants stay at trial limits on a production key, and only the R models have published prices
  3. Keep a trial key under 20 chat requests a minute and 1,000 calls a month, and do not use it for commercial work
  4. Set response_format with a json_schema for structured output, and tell the model to produce JSON when using json_object without a schema
  5. Ask the account Owner to turn off training under Data Controls in the dashboard before sending confidential prompts

Vertex AI (Gemini Enterprise Agent Platform)

  1. Call the global location on aiplatform.googleapis.com unless data residency requires a Region. The 429 guide says it spreads load and reduces errors
  2. Back off exponentially on 429 Resource exhausted. On Standard PayGo it means shared capacity is busy, not a fixed quota
  3. Send response_schema with response_mime_type: application/json. JSON mode alone doesn't guarantee valid output
  4. Set store to false on Interactions API calls. It defaults to true and keeps prompts and responses
  5. 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

Questions

Which is better for AI agents, Cohere Chat API (Command models) or Vertex AI (Gemini Enterprise Agent Platform)?

Vertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against Cohere Chat API (Command models)'s 65.6 (B), and leads in every scored category.

Do Cohere Chat API (Command models) and Vertex AI (Gemini Enterprise Agent Platform) need an API key?

Cohere Chat API (Command models) needs an API key. Vertex AI (Gemini Enterprise Agent Platform) takes an API key or an OAuth sign-in.

Can an agent call Cohere Chat API (Command models) and Vertex AI (Gemini Enterprise Agent Platform) without installing anything?

Yes. Cohere Chat API (Command models) has a hosted endpoint at https://api.cohere.com/v2/chat and Vertex AI (Gemini Enterprise Agent Platform) at https://aiplatform.googleapis.com/v1.

Other comparisons with Cohere Chat API (Command models) or Vertex AI (Gemini Enterprise Agent Platform)

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